Verified email at atu.ac.ir
Department of Industrial Management, Faculty of Management and Accounting
Allameh Tabataba’i University
Shakib Zohrehvandi, Mohammad Khalilzadeh, Maghsoud Amiri, and Shahram Shadrokh
Automation in Construction, ISSN: 09265805, Volume: 117, Published: September 2020 Elsevier BV
Maghsoud Amiri, Mohammad Hashemi-Tabatabaei, Mohammad Ghahremanloo, Mehdi Keshavarz-Ghorabaee, Edmundas Kazimieras Zavadskas, and Jurgita Antucheviciene
Applied Soft Computing Journal, ISSN: 15684946, Published: July 2020 Elsevier BV
Mohammad Ghahremanloo, Aliakbar Hasani, Maghsoud Amiri, Mohammad Hashemi-Tabatabaei, Mehdi Keshavarz-Ghorabaee, and Leonas Ustinovičius
Engineering Management in Production and Services, ISSN: 25436597, eISSN: 2543912X, Pages: 7-19, Published: 10 May 2020 Walter de Gruyter GmbH
AbstractHospitals are the most important and costly component of the healthcare system. Therefore, hospital performance evaluation (HPE) is an important issue for the managers of these centres. This paper presents a new approach for HPE that can be used to calculate the efficiency, effectiveness, and productivity of hospitals simultaneously. Efficiency refers to the ratio of inputs and outputs, effectiveness refers to the extent to which outputs align with predetermined goals, and productivity refers to the sum of both efficiency and effectiveness. To this end, a Data Envelopment Analysis (DEA) model is developed to simultaneously measure the efficiency, effectiveness, and productivity (DEA-EEP) of hospitals. DEA is a linear programming technique that in its traditional form, calculates the performance of similar decision-making units (DMUs) that have both inputs and outputs. In this study, the inputs are the number of health workers, the number of other staff, and the number of patient beds; while the outputs are the bed occupancy rate and the bed turnover rate. A target value is set for each output to measure the effectiveness of hospitals. The advantage of the developed model is the ability to provide a solution for non-productive units so that they can improve their performance by changing their inputs and outputs. In the case study, data of 11 hospitals in Tehran were evaluated for a 3-year period. Based on the results, some hospitals experienced an upward trend in the period, but the efficiency, effectiveness, and productivity scores of most hospitals fluctuated and did not have a growing trend. This indicates that although most hospitals sought to improve the quality of their services, they needed to take more serious steps.
Maghsoud Amiri and Mir Seyed Mohammad Mohsen Emamat
Informatica (Netherlands), ISSN: 08684952, Pages: 21-34, Published: 2020 Vilnius University Press
M. Amiri, M. Hashemi-Tabatabaei, M. Ghahremanloo, M. Keshavarz-Ghorabaee, E. K. Zavadskas, and A. Banaitis
International Journal of Sustainable Development and World Ecology, ISSN: 13504509, eISSN: 17452627, Pages: 1-18, Published: 2020 Informa UK Limited
Maedeh Mosayeb Motlagh, Parham Azimi, Maghsoud Amiri, and Golshan Madraki
Expert Systems with Applications, ISSN: 09574174, Volume: 138, Published: 30 December 2019 Elsevier BV
Abstract This research develops an expert system to addresses a novel problem in the literature of buffer allocation and production lines. We investigate real-world unreliable unbalanced production lines where all time-based parameters are probabilistic including time between parts arrivals, processing times, time between failures, repairing times, and setup times. The main contributions of the paper are a twofold. First and foremost, the mean processing times of workstations and buffer capacities, unlike the existing literature, are considered as decision variables in a multi-objective optimization problem which maximizes the throughput rate and minimizes the total buffer capacities as well as the total cost of the mean process time reductions. Secondly, an efficient methodology is developed that can precisely reflect a real-world system without any unrealistic and/or restrictive assumptions on the probabilistic nature of the system, which are commonly assumed in the existing literature. One of the greatest challenges in this research is to estimate the throughput rate function since it highly depends on the random behavior of the system. Thus, a simulation optimization approach is developed based on the Design of Experiments and Response Surface Methodology to fit a regression model for throughput rate. Finally, Non-dominated Sorting Genetic Algorithm (NSGA-II) and Non-dominated Ranked Genetic Algorithm (NRGA) are used to generate high-quality solutions for the aforementioned problem. This methodology is run on a real numerical case. The experimental results confirm the advantages of the proposed methodology. This methodology is an innovative expert system with a knowledge-base developed through this simulation optimization approach. This expert system can be applied to complex production line problems in large or small scale with different types of decision variables and objective functions. The application of this expert system is transformative to other manufacturing systems.
Hassan Hadipour, Maghsoud Amiri, and Mani Sharifi
Reliability Engineering and System Safety, ISSN: 09518320, Volume: 192, Published: December 2019 Elsevier BV
Abstract Redundancy allocation is one of the most common approaches to increase the system reliability. In this study, a new model is developed to maximize mean time to failure and to minimize the cost of a system. In general, many researchers are now considering the active redundancy even more than before; however, it is possible for a particular system design to utilize active redundancy and warm-standby redundancy as well. In this model, each subsystem can use both active and warm-standby strategies simultaneously. Moreover, the model allows for component mixing such that components of different types may be used in each subsystem. Thus, the aim of the proposed model is to select the best redundancy strategy, components’ types and levels of redundancy for each subsystem. The simulation and neural network methods are applied considering the structural complexity of the model and repairable components. In order to solve the problem, meta-heuristic of Multi Objective Water Flow algorithm (MOWFA) is proposed and compared to NSGA-II and NRGA. Also, for tuning the meta-heuristics parameters, the Taguchi design of experiments is employed. The algorithms are used to solve 32 test problems and the results are compared. Finally, the results are analyzed and discussed.
Mina Dehghani, Vahab Vahdat, Maghsoud Amiri, Elaheh Rabiei, and Seyedmohammad Salehi
Computers and Industrial Engineering, ISSN: 03608352, Volume: 138, Published: December 2019 Elsevier BV
Abstract Design of a reliable network in presence of flow loss has become the primary objective of today’s network designers. However, there are other important conflicting objectives that hinder the process of efficient network design. This study proposes a multi-objective optimization model for reliable communication flow networks, including maximizing the network reliability, minimizing total cost, and maximizing network flow, simultaneously. The total cost comprises the cost of construction of network arcs and the cost of flow, while arcs may fail to operate in full-capacity and may only function to a fraction of their capacity. The reliability-based network-design is modeled as a mixed-integer linear programming and solved by three metaheuristic multi-objective methods namely multi-objective particle swarm optimization (MOPSO) and two versions of non-dominated sorting genetic algorithm (i.e., NSGA-II and NSGA-III). In order to select the best compromise solution from the Pareto front members, a fuzzy-based mechanism is utilized. Finally, in order to measure the performance of the three algorithms, several numerical examples in small and large-scale are solved. The computational results indicate that NSGA-III is superior to MOPSO and NSGA-II in terms of convergence rate and running time especially for large-scale problems.
Ramin Golestaneh, Roxana Fekri, Maghsoud Amiri, and Rasoul Sajjad
Proceedings of 2019 15th Iran International Industrial Engineering Conference, IIIEC 2019, Pages: 7-13, Published: 22 May 2019 IEEE
Sepehr Ghazinoory, Maghsoud Amiri, Soroush Ghazinoori, and Parisa Alizadeh
Economics of Innovation and New Technology, ISSN: 10438599, eISSN: 14768364, Pages: 365-385, Published: 19 May 2019 Informa UK Limited
ABSTRACTA consistent mix of policy tools can solve complex policy problems. However, the diversity of policy instruments and their interactions make the analysis of various packages difficult. Mathematical methods can help policy makers to choose better alternatives. This article proposes a novel application of a multi-objective decision-making (MODM) method to design policy mixes and applies it to plan a policy mix for increasing business expenditure on research and development (BERD) in Iran. The interactions between the policy instruments were successfully modeled to design policy mix with maximized effectiveness and feasibility. Moreover, constraints regarding the consistency and diversity of instruments were added to the model. Using a genetic algorithm in MATLAB R2016a the optimum mix was searched, and the Pareto frontier was found for the different levels of total cost. The results of this research show that mathematical programing can be effectively used to handle the complexity of designing polic...
Samira Parsaiyan, Maghsoud Amiri, Parham Azimi, and Mohammad Taghi Taqhavi Fard
International Journal of Business Performance and Supply Chain Modelling, ISSN: 17589401, eISSN: 1758941X, Pages: 283-322, Published: 2019 Inderscience Publishers
Ehsan Dehghan, Maghsoud Amiri, Mohsen Shafiei Nikabadi, and Armin Jabbarzadeh
Journal of Intelligent and Fuzzy Systems, ISSN: 10641246, eISSN: 18758967, Pages: 6457-6470, Published: 2019 IOS Press
Pedram Pourkarim Guilani, Parham Azimi, Mani Sharifi, and Maghsoud Amiri
Scientia Iranica, ISSN: 10263098, eISSN: 23453605, Pages: 1023-1038, Published: 2019 SciTech Solutions
Reliability improvement for electronics and mechanical systems is vital for engineers in order to design of these systems. For this reason, there are many researches in this scope to help engineers in real world applications. One of the useful methods in reliability optimization is redundancy allocation problem (RAP). In the most previous works, the failure rates of system components are considered to be constant based on negative exponential distribution; whereas, nearly all systems in real world have components with time-dependent failure rates; i.e., the failure rates of system components will be changed time by time. In this paper, we have worked on a RAP for a system under k-out-of-n subsystems with time-dependent components failure rates based on Weibull distribution. Also, the redundancy policy of the proposed system is considered as mixed strategy and the optimization method was based on the simulation technique to obtain reliability function as implicit function. Finally, a branch and bound algorithm has been used to solve the model, exactly. 1 Corresponding author Email: P.Azimi@yahoo.com
Mehdi Keshavarz-Ghorabaee, Kannan Govindan, Maghsoud Amiri, Edmundas Kazimieras Zavadskas, and Jurgita Antuchevičienė
Journal of Environmental Engineering and Landscape Management, ISSN: 16486897, eISSN: 18224199, Pages: 187-200, Published: 2019 Vilnius Gediminas Technical University
One of the most essential topics for the present and future generations is sustainability. Today, because of threats made by traditional and old manufacturing practices, sustainability has become an essential topic in manufacturing companies. Attaining a sustainable manufacturing process requires making decisions about the strategies of manufacturing. In this paper, a novel integrated model is developed to evaluate sustainable manufacturing strategies. The proposed model is based upon two multi-criteria decision-making (MCDM) methods: WASPAS (Weighted Aggregated Sum Product ASsessment) and SECA (Simultaneous Evaluation of Criteria and Alternatives). Due to the uncertainty of evaluation process, we use interval type-2 fuzzy sets (IT2FSs). An example of evaluating sustainable manufacturing strategies is presented, and a sensitivity analysis is carried out for illustration of the developed approach and validation of it. The findings show the efficiency of the developed model, and based on the considered example, “Eco-efficiency” can be regarded as an effective strategy.
Mohammad Hashemi Tabatabaei, Maghsoud Amiri, Mohammad Ghahremanloo, Mehdi Keshavarz-Ghorabaee, Edmundas Kazimieras Zavadskas, and Jurgita Antucheviciene
International Journal of Computers, Communications and Control, ISSN: 18419836, eISSN: 18419844, Pages: 710-725, Published: 2019 Agora University of Oradea
Decision-making processes in different organizations often have a hierarchical and multilevel structure with various criteria and sub-criteria. The application of hierarchical decision-making has been increased in recent years in many different areas. Researchers have used different hierarchical decision-making methods through mathematical modeling. The best-worst method (BWM) is a multi-criteria evaluation methodology based on pairwise comparisons. In this paper, we introduce a new hierarchical BWM (HBWM) which consists of seven steps. In this new approach, the weights of the criteria and sub-criteria are obtained by using a novel integrated mathematical model. To analyze the proposed model, two numerical examples are provided. To show the performance of the introduced approach, a comparison is also made between the results of the HBWM and BWM methodologies. The analysis demonstrates that HBWM can effectively determine the weights of criteria and sub-criteria through an integrated model.
Transformations in Business and Economics, ISSN: 16484460, Pages: 197-214, Published: 2019
Ehsan Dehghan, Mohsen Shafiei Nikabadi, Maghsoud Amiri, and Armin Jabbarzadeh
Computers and Industrial Engineering, ISSN: 03608352, Volume: 123, Pages: 220-231, Published: September 2018 Elsevier BV
Abstract The main goal of this study is to address gap in the area of Closed-loop Supply Chain Network Design (CLSCND) under the hybrid uncertain conditions. To do this, a multi-product and multi-period model is developed in an edible oil supply chain. Since the proposed model includes two kinds of uncertain parameters, the scenario- and fuzzy-based parameters, a novel Robust Stochastic-Possibilistic Programming (RSPP) are proposed to cope with uncertain parameters, based on the Me measure. Furthermore, the performance of the RSPP model is reviewed, its weaknesses and strengths are studied, and it is compared with the other models. Finally, the usefulness and applicability of the RSPP model are tested by the real industrial case study.
Mojtaba Hemmati, Maghsoud Amiri, and Mostafa Zandieh
Quality and Reliability Engineering International, ISSN: 07488017, eISSN: 10991638, Pages: 278-297, Published: April 2018 Wiley
Mehdi Keshavarz-Ghorabaee, Maghsoud Amiri, Edmundas Zavadskas, Zenonas Turskis, and Jurgita Antucheviciene
Symmetry, eISSN: 20738994, Published: 1 April 2018 MDPI AG
Determination of subjective weights, which are based on the opinions and preferences of decision-makers, is one of the most important matters in the process of multi-criteria decision-making (MCDM). Step-wise Weight Assessment Ratio Analysis (SWARA) is an efficient method for obtaining the subjective weights of criteria in the MCDM problems. On the other hand, decision-makers may express their opinions with a degree of uncertainty. Using the symmetric interval type-2 fuzzy sets enables us to not only capture the uncertainty of information flexibly but also to perform computations simply. In this paper, we propose an extended SWARA method with symmetric interval type-2 fuzzy sets to determine the weights of criteria based on the opinions of a group of decision-makers. The weights determined by the proposed approach involve the uncertainty of decision-makers’ preferences and the symmetric form of the weights makes them more interpretable. To show the procedure of the proposed approach, it is used to determine the importance of intellectual capital dimensions and components in a company. The results show that the proposed approach is efficient in determining the subjective weights of criteria and capturing the uncertainty of information.
Mehdi Keshavarz-Ghorabaee, Maghsoud Amiri, Edmundas Zavadskas, Zenonas Turskis, and Jurgita Antucheviciene
Information (Switzerland), eISSN: 20782489, Published: 19 March 2018 MDPI AG
Selection of appropriate subcontractors for outsourcing is very important for the success of construction projects. This can improve the overall quality of projects and promote the qualification and reputation of the main contractors. The evaluation of subcontractors can be made by some experts or decision-makers with respect to some criteria. If this process is done in different time periods, it can be defined as a dynamic multi-criteria group decision-making (MCGDM) problem. In this study, we propose a new fuzzy dynamic MCGDM approach based on the EDAS (Evaluation based on Distance from Average Solution) method for subcontractor evaluation. In the procedure of the proposed approach, the sets of alternatives, criteria and decision-makers can be changed at different time periods. Also, the proposed approach gives more weight to newer decision information for aggregating the overall performance of alternatives. A numerical example is used to illustrate the proposed approach and show the application of it in subcontractor evaluation. The results demonstrate that the proposed approach is efficient and useful in real-world decision-making problems.
Proceedings of the International Conference on Industrial Engineering and Operations Management, eISSN: 21698767, Volume: 2018, Issue: SEP, Pages: 1043-1053, Published: 2018
Proceedings of the International Conference on Industrial Engineering and Operations Management, eISSN: 21698767, Volume: 2018, Issue: SEP, Pages: 1054-1061, Published: 2018
Mehdi Keshavarz Ghorabaee, Maghsoud Amiri, Edmundas Kazimieras Zavadskas, and Jurgita Antucheviciene
Archives of Civil and Mechanical Engineering, ISSN: 16449665, Pages: 32-49, Published: January 2018 Springer Science and Business Media LLC
Abstract Because of the possible harmful effects of construction equipment on the environment, evaluation of them can be considered as a helpful activity to move toward the sustainability in construction. This evaluation process could involve some alternatives and some criteria in a discrete decision space. In this study, a new hybrid multi-criteria decision-making (MCDM) approach is proposed to deal with this evaluation process in the fuzzy environment. We present fuzzy extensions of the SWARA (Step-wise Weight Assessment Ratio Analysis) and CRITIC (CRiteria Importance Through Intercriteria Correlation) methods for determining subjective and objective weights of criteria. Based on these extended methods and the fuzzy EDAS (Evaluation based on Distance from Average Solution) method, a new hybrid approach is proposed. In this approach, the subjective and objective criteria weights are combined to determine more justified weights for criteria. The proposed approach is applied to a case study of construction equipment evaluation with sustainability considerations. To examine the result of evaluation, a sensitivity analysis is performed based on varying criteria weights. A comparison is also made between the results of the proposed approach and some existing MCDM methods. These analyses show the stability and validity of the results and efficiency of the proposed approach.
KESHAVARZ-GHORABAEE MEHDI, AMIRI MAGHSOUD, ZAVADSKAS EDMUNDAS KAZIMIERAS, TURSKIS ZENONAS, and ANTUCHEVICIENE JURGITA
Economic Computation and Economic Cybernetics Studies and Research, ISSN: 0424267X, eISSN: 18423264, Pages: 121-134, Published: 2018 Bucharest University of Economic Studies
The rank reversal (RR) phenomenon could occur when new information about alternatives or criteria is added to the decision space of a discrete multi-criteria decision-making (MCDM) problem. If this addition leads to a change in the original rank of alternatives, the RR phenomenon occurs. In this study, we analyze the RR phenomenon in a new MCDM method called EDAS (Evaluation based on Distance from Average Solution). For this purpose, three RR indices are defined, and the efficiency of the EDAS method is compared with the TOPSIS method through a simulation-based analysis. The results show that the EDAS method is more efficient than the TOPSIS method with respect to the defined RR measures.
Mehdi Keshavarz-Ghorabaee, Maghsoud Amiri, Edmundas Kazimieras Zavadskas, Zenonas Turskis, and Jurgita Antuchevičienė
Baltic Journal of Road and Bridge Engineering, ISSN: 1822427X, eISSN: 18224288, Pages: 209-237, Published: 2018 Riga Technical University
Bridges are considered as essential structures of the transport infrastructures, which play an essential role in any road network. Therefore, the process of planning and designing bridges needs to be made efficiently. The design of bridges usually consists of two stages: conceptual design and detailed design. Designers make decisions on the overall form of the structure in the conceptual design process. This process is defined as Multi-Criteria Decision-Making problems. In this study, a modified fuzzy Technique for Order of Preference by Similarity to Ideal Solution method to deal with the conceptual design process under uncertainty is proposed. The proposed method uses an area-based deviation ratio to determine the degree of difference between alternatives and reference solutions of the Technique for Order of Preference by Similarity to Ideal Solution method. Using this ratio incorporates the effects of the membership functions into the evaluation process. To illustrate the procedure of the proposed method, an example of multi-criteria assessment of bridge design including three Multi-Criteria Decision-Making problems with quantitative and qualitative criteria is used. For validation of the results of the modified fuzzy Technique for Order of Preference by Similarity to Ideal Solution method, a comparative analysis is also made. The analysis shows that the results of the proposed method are consistent with the other method.
Mehdi KESHAVARZ-GHORABAEE, Maghsoud AMIRI, Edmundas Kazimieras ZAVADSKAS, Zenonas TURSKIS, and Jurgita ANTUCHEVICIENE
Informatica (Netherlands), ISSN: 08684952, Pages: 265-280, Published: 2018 Vilnius University Press
Mehdi Keshavarz Ghorabaee, Maghsoud Amiri, Edmundas Kazimieras Zavadskas, Zenonas Turskis, and Jurgita Antucheviciene
Computers and Industrial Engineering, ISSN: 03608352, Volume: 112, Pages: 156-174, Published: October 2017 Elsevier BV
A new approach is proposed for supplier evaluation and order allocation.Environmental and economic criteria are considered in the proposed approach.Interval type-2 fuzzy sets and the EDAS method are used for supplier evaluation.A multi-objective linear programming is proposed for order allocation.A sensitivity analysis is made to examine effects of environmental criteria on the model. Nowadays environmental performance of suppliers becomes more important because of competitive conditions. Besides, the economic performance has been a significant factor for companies to choose their suppliers. In this paper, a new integrated model is proposed for supplier evaluation and order allocation which considers both environmental and economic factors. We use the EDAS (Evaluation based on Distance from Average Solution) method and interval type-2 fuzzy sets for evaluation of suppliers with respect to environmental criteria. According to this evaluation two parameters are defined for each supplier: positive score and negative score. These parameters, together with cost parameters, are utilized to propose a multi-objective mathematical model for determination of order quantity from each supplier. A numerical example is used in this paper to show the applicability of the proposed integrated model. Also, a sensitivity analysis is made to examine the effect of weighting environmental criteria on total purchasing cost and quantity of order from each supplier. The results show that the proposed model is efficient and applicable for real-world problems.
Mehdi Keshavarz Ghorabaee, Maghsoud Amiri, Edmundas Kazimieras Zavadskas, Zenonas Turskis, and Jurgita Antucheviciene
Journal of Air Transport Management, ISSN: 09696997, Pages: 45-60, Published: August 2017 Elsevier BV
Evaluation of airlines based on service quality criteria can help to improve the processes of airlines, and also can give guidance to travel agencies to provide better choices for passengers and tourists. In this study, a hybrid simulation-based assignment approach is proposed to deal with multi-criteria decision-making problems with a group of decision-makers. A probability distribution is used to model decision-makersâ€™ opinions and constructing a stochastic decision matrix. Then some efficient multi-criteria decision-making methods are utilized for evaluating alternatives in a simulation process. The proposed approach is applied to a problem of evaluation of five airlines with respect to opinions of 58 experts on 28 criteria. The results show the efficiency of the proposed to handle decision-making problems with a large number of experts. Moreover, the evaluation results are more reliable than the other decision-making approaches because of simulating decision-makersâ€™ opinions, using multiple methods and evaluating based on aggregative results.
Mehdi KESHAVARZ GHORABAEE, Maghsoud AMIRI, Laya OLFAT, and S. M. Ali KHATAMI FIROUZABADI
Technological and Economic Development of Economy, ISSN: 20294913, eISSN: 20294921, Pages: 520-548, Published: 4 May 2017 Vilnius Gediminas Technical University
Integration of reverse logistics processes into supply chain network design can help to achieve a network that incorporates environmental factors as well as economic factors. In this study, a new integrated approach is proposed to address designing a multi-product, multi-period supply chain network with reverse logistics. The framework of the proposed approach includes green supplier evaluation and a mathematical model in an uncertain environment. To the best of our knowledge, integration of green supplier evaluation into the designing supply chain network with reverse logistics has not been considered in the literature. This integration can help to incorporate experts’ opinions about environmental impact of suppliers in the network design. Minimization of total cost and maximization of total greenness score of purchased raw materials/components are two objectives of the model. The fuzzy EDAS method is used to determine the greenness scores of suppliers. Also, demand of customers and capacity of suppliers are defined using fuzzy numbers and a fuzzy method is used to obtain trade-off solutions. The proposed approach is applied to designing the supply chain network of a home appliance company. The results show that the proposed approach is feasible and efficient to obtain solutions to design the supply chain network.
Farjam Kayedpour, Maghsoud Amiri, Mahmoud Rafizadeh, and Arash Shahryari Nia
Reliability Engineering and System Safety, ISSN: 09518320, Volume: 160, Pages: 11-20, Published: 1 April 2017 Elsevier BV
Many Studies have been conducted on Redundancy Allocation Problem (RAP), but only a few of them have considered designing systems which operate for a certain period of time. Such temporary systems are not meant to operate for a long period of time (e.g. a manufacturing cell designed to produce a unique product with a small window of opportunity). Due to this fact, the investigation of the reliability at an infinite time will not be helpful; instead designing a system which perform optimally in a short period of time is of importance. additionally RAP's are inherently complex and classified as NP-Hard, as a result most proposed approaches, consider a set of simplified assumptions. Among these assumptions are the calculation of availability in the steady state (a time in which a system becomes completely stable), the use of non-repairable components, and setting predetermined configuration strategy (parallel, cold or warm standby subsystems). Unfortunately, these simplified assumptions do not conform to the real world conditions. Therefore, this article intends to develop an integrated algorithm to solve the reliability design problem considering instantaneous availability, repairable components, and the selection of configuration strategies based on the Markov processes and NSGA-II algorithm.
Mehdi Keshavarz Ghorabaee, Maghsoud Amiri, Edmundas Kazimieras Zavadskas, and Jurgita Antuchevičienė
Transport, ISSN: 16484142, eISSN: 16483480, Pages: 66-78, Published: 2 January 2017 Vilnius Gediminas Technical University
The assessment of Third-Party Logistics (3PL) provider becomes an important issue for enterprises trying to achieve operational efficiency and customer service improvement as well as capital expenditure and logistics costs reduction. It can be said that evaluation and selection of an appropriate 3PL provider is a kind of Multi-Criteria Decision-Making (MCDM) problem. Uncertainty is an unavoidable part of information in the decision-making process. Interval Type-2 Fuzzy Sets (IT2FSs) are very flexible to model the uncertainty of the MCDM problems. In this study, a new integrated approach based on the criteria Importance Through Inter-criteria Correlation (CRITIC) and Weighted Aggregated Sum Product assessment (WASPAS) methods is proposed to evaluate 3PL providers with IT2FSs. In the proposed approach, objective weights resulted from the CRITIC method are combined with subjective weights expressed by decision-makers (dms) to determine more realistic weights for criteria. A computational study is performed to illustrate the proposed approach and the applicability of it. In addition, a sensitivity analysis is carried out using different sets of criteria weights to demonstrate the stability of the proposed approach. The results show the stability of ranking results and prove the efficiency of the proposed approach to handle MCDM problems with IT2FSs.
Mehdi KESHAVARZ GHORABAEE, Maghsoud AMIRI, Edmundas Kazimieras ZAVADSKAS, Reyhaneh HOOSHMAND, and Jurgita ANTUCHEVIČIENĖ
Journal of Business Economics and Management, ISSN: 16111699, eISSN: 20294433, Pages: 1-19, Published: 2 January 2017 Vilnius Gediminas Technical University
One of the important activities of a company that can increase its competitiveness is market segment evaluation and selection (mse/mss). We can usually consider mse/mss as a multi-criteria decision-making (mcdm) problem, and so we need to use an mcdm method to handle it. Uncertainty is one of the important factors that can affect the process of decision-making. Fuzzy mcdm approached have been designed to deal with the uncertainty of decision-making problems. In this study, a fuzzy extension of the codas (combinative distance-based assessment) method is proposed to solve multi-criteria group decision-making problems. We use linguistic variables and trapezoidal fuzzy numbers to extend the codas method. The proposed fuzzy codas method is applied to an example of market segment evaluation and selection problem under uncertainty. To validate the results, a comparison is performed between the fuzzy codas and two other mcdm methods (fuzzy edas and fuzzy topsis). A sensitivity analysis is also carried out to demonstrate the stability of the results of the fuzz codas. For this aim, ten sets of criteria weights are randomly generated and the example is solved using each set separately. The results of the comparison and the sensitivity analysis show that the proposed fuzzy codas method gives valid and stable results.
Mehdi KESHAVARZ GHORABAEE, , Maghsoud AMIRI, Zenonas TURSKIS, , and
Informatica (Netherlands), ISSN: 08684952, Pages: 79-104, Published: 2017 Vilnius University Press
The redundancy allocation problem (RAP) has been studied for many different system structures, objective functions, and distribution assumptions. In this paper, we present a problem formulation and a solution methodology to maximize the system steady-state availability and minimize the system cost for the repairable series-parallel system designs. In the proposed approach, the components’ time-to-failure (TTF) and time-to-repair (TTR) can follow any distribution such as the Gamma, Normal, Weibull, etc. We estimate an approximation of the steady-state availability of each subsystem in the series-parallel system with an individual meta-model. Design of experiment (DOE), simulation and the stepwise regression are used to build these meta-models. Face centred design, which is a type of central composite design is used to design experiments. According to a max–min approach, obtained meta-models are utilized for modelling the problem alongside the cost function of the system. We use the augmented ε-constraint method to reformulate the problem and solve the model. An illustrative example which uses the Gamma distribution for TTF and TTR is explained to represent the performance of the proposed approach. The results of the example show that the proposed approach has a good performance to obtain Pareto (near-Pareto) optimal solutions (system configurations).
International Journal of Economic Perspectives, eISSN: 13071637, Pages: 1737-1747, Published: 2017
Mehdi Keshavarz Ghorabaee, Maghsoud Amiri, Edmundas Kazimieras Zavadskas, and Jurgita Antucheviciene
Economic Research-Ekonomska Istrazivanja, ISSN: 1331677X, Pages: 1073-1118, Published: 2017 Informa UK Limited
AbstractIn past years, the multi-attribute decision-making (MADM) approaches have been extensively applied by researchers to the supplier evaluation and selection problem. Many of these studies were performed in an uncertain environment described by fuzzy sets. This study provides a review of applications of MADM approaches for evaluation and selection of suppliers in a fuzzy environment. To this aim, a total of 339 publications were examined, including papers in peer-reviewed journals and reputable conferences and also some book chapters over the period of 2001 to 2016. These publications were extracted from many online databases and classified in some categories and subcategories according to the MADM approaches, and then they were analysed based on the frequency of approaches, number of citations, year of publication, country of origin and publishing journals. The results of this study show that the AHP and TOPSIS methods are the most popular approaches. Moreover, China and Taiwan are the top countries...
Mehdi Keshavarz Ghorabaee, Maghsoud Amiri, Edmundas Kazimieras Zavadskas, and Zenonas Turskis
E a M: Ekonomie a Management, ISSN: 12123609, Pages: 48-68, Published: 2017 Technical University of Liberec
Multi-criteria decision-making (MCDM) methods are very useful in the real-world decision-making problems. We are usually confronted with the decision-making process in an uncertain environment, and the fuzzy set theory is an effi cient tool to handle this uncertainty. Interval type-2 fuzzy sets are one of the extensions of the fuzzy sets which are very fl exible to model an uncertain environment. This study is related to MCDM problems within the context of interval type-2 fuzzy sets (IT2FSs). The evaluation based on distance from average solution (EDAS) method is a new and effi cient MCDM method, and assessment of alternatives in this method is based on the distance of them from average solution with respect to all criteria. In the EDAS method, each alternative has positive and negative distances which are used to determine the appraisal score of it. In this research, we present an extended EDAS method, which is named EDAS-IT2FSs, for dealing with multicriteria group decision-making problems with interval type-2 fuzzy sets. Basic concepts of interval type-2 fuzzy sets and the arithmetic operations of trapezoidal IT2FSs are used to develop the extended EDAS method. A numerical example of multi-criteria subcontractor evaluation problem is used to illustrate the process of using the extended EDAS method. The example involves eight subcontractors that need to be evaluated with respect to seven criteria. A comparison and a sensitivity analysis based on different sets of criteria weights are also performed to show the validity of the proposed method. The results of these analyses show the effi ciency and stability of the extended EDAS method.
Mehdi Keshavarz Ghorabaee, Maghsoud Amiri, Edmundas Kazimieras Zavadskas, Zenonas Turskis, and Jurgita Antucheviciene
Journal of Intelligent and Fuzzy Systems, ISSN: 10641246, eISSN: 18758967, Pages: 1627-1638, Published: 2017 IOS Press
Discrete stochastic multi-criteria decision-making (MCDM) can be used to handle many real-life decision-making problems. The Evaluation Based on Distance from Average Solution (EDAS) is a new and efficient MCDM method. The desirability of alternatives in this method is determined based on distances of them from an average solution. Because the average solution is determined by an arithmetic mean in this method, the EDAS method can be efficient for solving stochastic problems. In this paper, a stochastic EDAS method is proposed to handle problems in which the performance values of alternatives on each criterion follow the normal distribution. Based on the proposed method, we can obtain optimistic and pessimistic appraisal scores for evaluation of alternatives and consider the uncertainty of decision-making data. We present a graphical example to illustrate the proposed method and a practical example of performance evaluation of bank branches to show the applicability of it. According to the analyses made, the proposed method is efficient and the results are valid.
Gholamhossein Soleimani, Magsod Amiri, Seyed Mohammadali Khatami, and MohammadJavad Isfahani
Industrial Engineering and Management Systems, ISSN: 15987248, eISSN: 22346473, Pages: 290-297, Published: 1 December 2016 Korean Institute of Industrial Engineers
The successful transfer of technology, needs to recognize the industrial purposes, resources, technology, innovation and the mode of transmission, methods of transmission, influential factors, it’s how to recruit and how to develop, and each of these cognitive relies on special expertise. One of the important technologies is automotive technology, and s technology is important for the transition and its development in recent years. Hence, in this paper, after studying Iran and the world’s automotive and emerging technologies situation, the status of commercial vehicles and s technology model are studied based on external models, technical specifications, and cost. In this way, we examine the incidence and the applicability of the technology used in the production of heavy-duty vehicles, in recent years, with the passage of time, and we examine the technology lifecycle, from the perspective of physical characteristics and technical features. The results show that the technology of the studied heavy-duty vehicles (Titan) is close to the time of his fall, because spending puberty, so, according to the investigation of new technologies, we should strive to create changes in vehicle technology.
Mehdi Keshavarz Ghorabaee, Edmundas Kazimieras Zavadskas, Maghsoud Amiri, and Ahmad Esmaeili
Journal of Cleaner Production, ISSN: 09596526, Volume: 137, Pages: 213-229, Published: 20 November 2016 Elsevier BV
Abstract The main goal of green supply chain management (GSCM) is to reduce the negative environmental impacts in all activities and stages of a supply chain. Evaluation of suppliers in a supply chain according to environmental criteria can help us to achieve this goal of GSCM. Since this evaluation usually comprises some alternatives and some criteria, green supplier selection (GSS) could be considered as a multi-criteria decision-making (MCDM) problem. To handle the uncertainty of information in an MCDM problem, the theory of fuzzy sets is an effective tool. Interval type-2 fuzzy sets (IT2FSs), which are characterized by an interval membership function, is very flexible to model the uncertainty of the MCDM problems. In this study, a new integrated approach based on Weighted Aggregated Sum Product Assessment (WASPAS) method, is proposed to deal with multi-criteria group decision-making problems with IT2FSs. This approach is based on the operators of IT2FSs, some modifications in the classical WASPAS method and a new procedure for calculation of criteria weights. In the procedure of calculation of criteria weights, we combine the subjective weights expressed by decision-makers with objective weights resulted from an entropy method to obtain more realistic weights. To show the applicability of the proposed approach in the real-world MCDM problems, a green supplier selection problem is used. We perform a sensitivity analysis with different weights of criteria and different values of method's parameters to show the stability of the proposed approach. This analysis shows that combining the subjective and objective weights can help to increase the stability of the proposed approach with different weights of criteria. A comparison is also made between the results of the proposed approach and some existing methods for validating the proposed approach. This analysis shows that the proposed approach is efficient and well consistent with the other methods.
Laya Olfat, Maghsoud Amiri, Jahanyar Bamdad Soufi, and Mahsa Pishdar
Journal of Air Transport Management, ISSN: 09696997, Pages: 272-290, Published: 1 October 2016 Elsevier BV
In this paper, sustainability of airports is considered through a multi-perspective, multi-system, and multi-process operation. It is explored how an extension of fuzzy dynamic network performance measurement approach helps to determine the efficiency performance of an airport system. In this way, a three-pronged approach is intended which considers the internal functions of an airport, functions affecting the community and functions related to the passengers simultaneously. This novel combination makes it possible to have a comprehensive evaluation of airports' performance. Besides, fuzzy extension of SBM dynamic network approach makes it possible to deal better with the vagueness of variables during analysis. So, this extension is valuable from both technical and conceptual aspects which in turn provide useful information and insights for the future design of holistic strategies connected with sustainable development of airports where ever they are.
Mohsen Rahimi Mazrae Shahi, Elnaz Fallah Mehdipour, and Maghsoud Amiri
International Transactions in Operational Research, ISSN: 09696016, eISSN: 14753995, Pages: 797-811, Published: 1 July 2016 Wiley
This paper presents a technique based on discrete-event simulation and response surface methodology to model and then optimize the schedule of subway train travels. The aim of this study is to find appropriate headways—time intervals between the travels of two consecutive trains—at different hours in order to optimize average passenger travel time and rate of carriage fullness. For physical reasons and the observance of safety standards, an increase in the train speed in order to decrease average passenger travel time may not exceed some specified limits. One of the ways to decrease this average is to appropriately adjust headways of trains in the schedule. For this purpose, a metamodel of multinomial type is fitted to the data obtained from simulation tests to describe the relation between input variables (headways) and output variables (average passenger travel time in system and carriage fullness rate), and then optimal combinations of input variables are obtained using a weighed metric method and sequential quadratic programming.
Rafi Rahanandeh Poor Langroodi and Maghsoud Amiri
Expert Systems with Applications, ISSN: 09574174, Pages: 231-244, Published: 1 June 2016 Elsevier BV
SD approach is used for multi-level, multi-product, multi region supply chain under demand uncertainty.The model is constructed in two distinctive sections including order placement and order fulfillment.The numerical example is applied for showing the outputs of the model.The model is analyzed in five cases to show the performance of each level in each region. It is highly crucial to design a supply chain in a way that determines to what extent each level should direct orders to the next level and, in cases where several next levels exist, which next level should be selected for such transmission of orders. The main significance of the proposed model is to choose an appropriate region for order placement and also investigate when a level in a specific region is disrupted what happens to the other levels in other regions. Also the main impact of this article is pertaining to managerial decisions that if a level in supply chain is shut down and disrupted what they should do Therefore, in the present study, system dynamics approach is used to design a five-level supply chain consisting of retailer, final product distributor, manufacturer, material distributor, and supplier in four different regions by specifying the amount of orders placed by each level at each region as well as the next level at each region that should receive these orders. The developed model is kind of multi-product model in which initial customer demand for any product is a random variable. There is only one entity in each region at every level, except for the number of material distributor(s) and supplier(s) which equals the number of raw material item(s). Finally, a numerical example is presented to discuss the result for normal conditions, oscillating demands, variations in price, changes in costs, and a combination of these variations which may vary depending on changes in the how orders are placed.
Maghsoud Amiri and Mostafa Khajeh
Journal of Industrial Engineering International, ISSN: 17355702, eISSN: 2251712X, Pages: 61-69, Published: 2016 Springer Science and Business Media LLC
Bi-objective optimization of the availability allocation problem in a series–parallel system with repairable components is aimed in this paper. The two objectives of the problem are the availability of the system and the total cost of the system. Regarding the previous studies in series–parallel systems, the main contribution of this study is to expand the redundancy allocation problems to systems that have repairable components. Therefore, the considered systems in this paper are the systems that have repairable components in their configurations and subsystems. Due to the complexity of the model, a meta-heuristic method called as non-dominated sorting genetic algorithm is applied to find Pareto front. After finding the Pareto front, a procedure is used to select the best solution from the Pareto front.
Economic Computation and Economic Cybernetics Studies and Research, ISSN: 0424267X, eISSN: 18423264, Pages: 39-68, Published: 2016
Transformations in Business and Economics, ISSN: 16484460, Pages: 76-95, Published: 2016
Mehdi Keshavarz Ghorabaee, Edmundas Kazimieras Zavadskas, Maghsoud Amiri, and Zenonas Turskis
International Journal of Computers, Communications and Control, ISSN: 18419836, eISSN: 18419844, Pages: 358-371, Published: 2016 Agora University of Oradea
In the real-world problems, we are likely confronted with some alternatives that eed to be evaluated with respect to multiple conflicting criteria. Multi-criteria ecision-making (MCDM) refers to making decisions in such a situation. There are any methods and techniques available for solving MCDM problems. The evaluation ased on distance from average solution (EDAS) method is an efficient multi-criteria ecision-making method. Because the uncertainty is usually an inevitable part of he MCDM problems, fuzzy MCDM methods can be very useful for dealing with the eal-world decision-making problems. In this study, we extend the EDAS method o handle the MCDM problems in the fuzzy environment. A case study of supplier election is used to show the procedure of the proposed method and applicability of t. Also, we perform a sensitivity analysis by using simulated weights for criteria to xamine the stability and validity of the results of the proposed method. The results f this study show that the extended fuzzy EDAS method is efficient and has good tability for solving MCDM problems.
Mehdi Keshavarz Ghorabaee, Maghsoud Amiri, and Parham Azimi
Applied Mathematical Modelling, ISSN: 0307904X, Pages: 6396-6409, Published: 15 October 2015 Elsevier BV
Abstract Reliability optimization problem is an important type of optimization problems that has many practical applications in the real-world systems such as manufacturing systems, telecommunication systems, transformation systems and electrical systems. This research focuses on redundancy allocation problem (RAP) that is a special type of reliability optimization problems. A bi-objective RAP, which is related to a system of s independent k-out-of-n subsystems in series, is considered in this study. Maximization of the system reliability and minimization of the system cost are the objectives of the problem, and the system is constrained by a predefined weight. The components of a subsystem are supposed to be non identical. To deal with this problem, we propose some multi-objective meta-heuristic algorithms based on the elitist non-dominated sorting genetic algorithm (NSGA-II). New modified methods of diversity preservation and constraint handling are introduced in this study. According to these methods and some existing methods, we propose four multi-objective genetic algorithms for solving the considered problem. A numerical example, a statistical method and three performance metrics are utilized for analyzing and comparing the performance of these four genetic algorithms. The comparison represents the positive effect of modified methods of diversity preservation and constraint handling on the performance of the algorithms.
IIE Annual Conference and Expo 2015, Pages: 1916-1925, Published: 2015
IIE Annual Conference and Expo 2015, Pages: 1175-1184, Published: 2015
Mehdi Keshavarz Ghorabaee, Maghsoud Amiri, Jamshid Salehi Sadaghiani, and Edmundas Kazimieras Zavadskas
International Journal of Information Technology and Decision Making, ISSN: 02196220, Pages: 993-1016, Published: 1 September 2015 World Scientific Pub Co Pte Lt
Project selection can be a real problem of the multi-criteria group decision making if a group of decision makers express their preferences depending on the nature of the alternatives and different criteria with respect to their knowledge about them. The purpose of the project selection process is to analyze project viability and to approve or reject project proposals based on established criteria. Such decisions are often complex, because they require the identification, consideration and analysis of many tangible and intangible factors. This paper presents a multi-criteria group decision-making approach for project selection problem in the type-2 fuzzy environment. The proposed method is an extended version of Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method with interval type-2 fuzzy numbers; it is called type-2 fuzzy VIKOR (T2F-VIKOR). A stepwise procedure is used for ranking and evaluating the alternatives in the developed method, and the best solution is selected considering both the beneficial and nonbeneficial criteria. An illustrative example is presented to show the applicability of the proposed approach in the project selection problems, and the results are analyzed. The results are compared with some existing methods to show the validity of the extended method. We also utilize six sets of criteria weights for analyzing the stability of the proposed method. These analyses show that the obtained results of the proposed method are relatively consistent with other methods and have good stability in different criteria weights.
Khalil Sajjadi, Mohammad Ali Khatami Firuzabadi, Maghsud Amiri, and Jamshid Salehi Sadaghiani
International Journal of Electronic Customer Relationship Management, ISSN: 17500664, eISSN: 17500672, Pages: 73-86, Published: 2015 Inderscience Publishers
Amir Hassanzadeh, Ahmad Jafarian, and Maghsoud Amiri
Applied Mathematical Modelling, ISSN: 0307904X, Issue: 9-10, Pages: 2353-2365, Published: 1 May 2014 Elsevier BV
Abstract The “bullwhip” effect is a major cause of supply chain deficiencies. This phenomenon refers to grow the amplification of demand or inventory variability as it moves up the supply chain. Supply chain managers experience this variance amplification in both inventory levels and orders. Other side, dampening variance in orders may have a negative impact on customer service due to the increase in the inventory variance. This paper with simulating a three stage supply chains consisting of a single retailer, single wholesaler and single manufacturer under both centralized and decentralized chains. In this paper, it is intended to analysis the causes of bullwhip effect from two dimensions of order and inventory variance using the response surface methodology. The results show that in both supply chains, rationing factor is considered as the least important cause of bullwhip effect. While the wholesaler’s order batching and the chain’s order batching are considered as the main causes for the bullwhip effect in the decentralized and centralized chains, respectively.
E. Fallah-Mehdipour, M. Amiri, and J. Salehi Sadaghiyani
Journal of Management in Engineering, ISSN: 0742597X, Pages: 272-273, Published: 1 March 2014 American Society of Civil Engineers (ASCE)
Do your table titles/figure captions cite other sources?If you used a figure/table from another source, written permission for print and online use must be attached in PDF format. Permission letters must state that permission is granted in both forms of media. If you used data from another source to create your own figure/table, the data is adapted and therefore obtaining permission is not required. There is no table titles/figure captions cite other sources.
Shide Sadat HASHEMI, , Seyed Hossein RAZAVI HAJIAGHA, Maghsoud AMIRI, , and
Informatica (Netherlands), ISSN: 08684952, Pages: 21-36, Published: 25 January 2014 Vilnius University Press
Maghsoud Amiri, Laya Olfat, and Mehdi Keshavarz Ghorabaee
International Journal of Advanced Manufacturing Technology, ISSN: 02683768, eISSN: 14333015, Issue: 1-4, Pages: 439-446, Published: April 2014 Springer Science and Business Media LLC
This paper considers a single machine scheduling problem, with the objective of minimizing a linear combination of total tardiness and waiting time variance in which the idle time is not allowed. Minimizing total tardiness is always regarded as one of the most significant performance criteria in practical systems to avoid penalty costs of tardiness, and waiting time variance is an important criterion in establishing quality of service (QoS) in many systems. Each of these criteria is known to be non-deterministic polynomial-time hard (NP-hard); therefore, the linear combination of them is NP-hard too. For this problem, we developed a genetic algorithm (GA) by applying its general structure that further improves the initial population, utilizing some of heuristic algorithms. The GA is shown experimentally to perform well by testing on various instances.
Mehdi Keshavarz Ghorabaee, Maghsoud Amiri, Jamshid Salehi Sadaghiani, and Golnoosh Hassani Goodarzi
International Journal of Advanced Manufacturing Technology, ISSN: 02683768, eISSN: 14333015, Issue: 5-8, Pages: 1115-1130, Published: 15 October 2014 Springer Science and Business Media LLC
Supplier selection is one of the most critical activities of purchasing management in a supply chain because of the key role of supplier’s performance in achieving the objectives of a supply chain. Supplier selection problem requires a trade-off between multiple criteria exhibiting vagueness and imprecision with the involvement of a group of experts. This paper presents a multiple criteria group decision-making approach for supplier selection problem in the context of interval type-2 fuzzy sets. A new method for ranking interval type-2 fuzzy numbers, based on the centroid of fuzzy sets, is proposed and compared with some methods. The proposed ranking method is used for extending complex proportional assessment (COPRAS) method for group decision-making with interval type-2 fuzzy numbers. The developed method uses a stepwise procedure for ranking and evaluating the alternatives, in terms of significance and utility degree, and selects the best solution considering both the positive-ideal and the negative-ideal solutions. To demonstrate the applicability of the proposed approach in supplier selection problems, an illustrative example is presented and the results are analyzed.
Ashraf Sadat Pasandideh, Reza Salami, Jahanyar Bamdad Soofi, and Maghsud Amiri
Research Journal of Applied Sciences, Engineering and Technology, ISSN: 20407459, eISSN: 20407467, Pages: 4413-4423, Published: 15 December 2013 Maxwell Scientific Publication Corp.
This study aims at designing a model for dynamic capabilities evaluation in equipment manufacturing enterprises of Iran power industry. In so doing, enablers and indices of dynamic capabilities four elements (i.e., seizing opportunities, sensing opportunities, innovation implementation and reconfiguration) are identified. Since dynamic capabilities literature is rooted in developed countries, localization of dynamic capability concepts in Iran as a developing country and in the power industry as a main infrastructure of development is a matter of great magnitude. Considering data gathered from more than 100 power industry equipment manufacturers in Iran and gaining the opinions of experts in such fields as innovation management and technology development, the model has been designed and its accuracy will be assessed in the present study.
Nima Zoraghi, Maghsoud Amiri, Golnaz Talebi, and Mahdi Zowghi
Journal of Industrial Engineering International, ISSN: 17355702, eISSN: 2251712X, Published: 1 December 2013 Springer Science and Business Media LLC
This paper presents a fuzzy multi-criteria decision-making (FMCDM) model by integrating both subjective and objective weights for ranking and evaluating the service quality in hotels. The objective method selects weights of criteria through mathematical calculation, while the subjective method uses judgments of decision makers. In this paper, we use a combination of weights obtained by both approaches in evaluating service quality in hotel industries. A real case study that considered ranking five hotels is illustrated. Examples are shown to indicate capabilities of the proposed method.
Life Science Journal, ISSN: 10978135, Issue: SUPPL 8, Pages: 70-91, Published: 25 July 2013
Farhaneh Golozari, Azizollah Jafari, and Maghsoud Amiri
International Journal of Advanced Manufacturing Technology, ISSN: 02683768, eISSN: 14333015, Issue: 5-8, Pages: 1791-1807, Published: July 2013 Springer Science and Business Media LLC
In the field of supply chain management and logistics, using vehicles to deliver products from depots to customers is one of the major operations. Before using vehicles, optimizing the location of depots is necessary in a location-routing problem (LRP). Also, before transportation products, optimizing the routing of vehicles is required so as to provide a low-cost and efficient service for customers. In this paper, the mathematical modelling of LRP is developed according to the existing condition and constraint in the real world. Maximum travelling time constraint is added, and we apply fuzzy numbers to determine customer demands, travelling time and drop time. The objective is to open a subset of depots to assign customers to these depots and to design vehicle routes, in order to minimize both the cost of open depots and the total cost of the routes. The proposed problem is modelled as a fuzzy linear programming (FLP), by applying the fuzzy ranking function method; the proposed FLP is converted to an exact linear programming (LP). A Lingo solver is used to solve this LP model in very small size. LRP is an non-deterministic polynomial-time hard (NP-Hard) problem, and because of the limitation of Lingo solver in solving medium, and large-size numerical examples, a hybrid algorithm including simulated annealing and mutation operator is proposed to solve these numerical examples. Also, a heuristic algorithm is proposed to find a suitable initial solution which is used in hybrid algorithm. At the end, a different analysis of the applied algorithm and a proposed model are introduced.
Saeid Fallah‐Jamshidi and Maghsoud Amiri
International Journal of Production Research, ISSN: 00207543, eISSN: 1366588X, Pages: 652-666, Published: 1 February 2013 Informa UK Limited
Of late, attempts are being made to optimise production system problems by minimum cost. A good available device in this area is response surface methodology. This methodology combines experimental designs and statistical techniques for empirical model building and optimising. In most situations simulated models for real world problems are non‐linear multi‐response, while responses are conflicting. The simultaneous optimisation of several conflicting responses is computationally expensive. So this makes the problem solving extremely complex. Since few attempts have been made to scrutinise this domain, in this paper the nonlinear continuous multi‐response problem is investigated. In order to tackle multi‐response optimisation difficulties, we propose a new hybrid meta heuristic based on the imperialist competitive algorithm. It simulates a socio–economical procedure, imperialistic competition. When there are some non‐dominated solutions in searching space, a technique for order performance by similarity to...
S. Meysam Mousavi, Behnam Vahdani, R. Tavakkoli-Moghaddam, S. Ebrahimnejad, and M. Amiri
International Journal of Advanced Manufacturing Technology, ISSN: 02683768, eISSN: 14333015, Issue: 9-12, Pages: 1263-1273, Published: February 2013 Springer Science and Business Media LLC
This paper presents a multi-stage decision-making process for multiple attributes analysis under an interval-valued fuzzy environment. The proposed method does not demand weights of conflicting attributes through the decision-making process under uncertainty. The performance ratings of potential alternatives with respect to selected conflicting attributes are first described by linguistic terms and then are represented as interval-valued triangular fuzzy numbers. Second, an outranking matrix is proposed to denote the frequency with which one potential alternative dominates all the other alternatives according to each selected attribute. Consequently, the outranking matrix is triangularized in order to provide an implicit preordering or provisional order of potential alternatives under uncertainty. Finally, the tentative order of alternatives undergoes different operations of the screening and balancing that requires sequential application of a balancing principle to the advantages–disadvantages table. It hybridizes the conflicting attributes with the pair-wise comparisons of the potential alternatives for the multiple attributes analysis. Furthermore, an application example is used for the decision-making in a selection problem to illustrate the feasibility and applicability of proposed method in an interval-valued fuzzy environment.
A. Hajnoori, M. Amiri, and A. Alimi
Decision Science Letters, ISSN: 19295804, eISSN: 19295812, Pages: 175-184, Published: 2013 Growing Science
Article history: Received March 2, 2013 Received in Revised Format April 14, 2013 Accepted April 16, 2013 Available online April 17 2013 Portfolio optimization problem follows the calculation of investment income per share, based on return and risk criteria. Since stock risk is achieved by calculating its return, which is itself computed based on stock price, it is essential to forecast the stock price, efficiently. In this paper, in order to predict the stock price, grey fuzzy technique with high efficiency is employed. The proposed study of this paper calculates the return and risk of each asset and portfolio optimization model is developed based on cardinality constraint and investment income per share. To solve the resulted model, Invasive Weed Optimization (IWO) algorithm is applied. In an example this algorithm is compared with other metaheuristic algorithms such as Imperialist Competitive Algorithm (ICA), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The results show that the applied algorithm performs significantly better than other algorithms. © 2013 Growing Science Ltd. All rights reserved.
Morteza Parhizkari, Maghsoud Amirib, and Morteza Mousakhani
Decision Science Letters, ISSN: 19295804, eISSN: 19295812, Pages: 185-190, Published: 2013 Growing Science
Selection of an appropriate supplier along with planning a good inventory system has become an area of open research for the past few years. In this paper, we present a multi objective decision making supplier and inventory management model where two objectives including the quality and offering price of supplier are minimized, simultaneously. The proposed model is formulated as mixed integer programming and it is converted into an ordinary single objective function using Lp-Norm. In order to find efficient solution, we use NSGA-II as meta-heuristic technique and the performance of the proposed model is examined using some instances. The preliminary results indicate that both Lp-Norm and NSGA-II methods can be used to handle problems in various sizes.
Mehdi Seifbarghy, Mandana Amiri and Mohammad Heydari
Scientia Iranica, ISSN: 10263098, Pages: 801-810, Published: June 2013
Abstract The inventory system under consideration consists of one central warehouse and a few non-identical retailers controlled by a continuous review inventory policy ( R , Q ). The retailers face an independent Poisson demand. Order transportation time from the central warehouse to each retailer is assumed to be constant. Also, the lead time for replenishing orders from an external supplier is assumed to be constant for the warehouse. Unsatisfied demands are assumed to be lost at the retailers and unsatisfied retailer orders are backordered at the warehouse. The cost function of the system was estimated utilizing a Response Surface Method (RSM) in the case of four retailers, and, in this regard, two linear and nonlinear regression models were developed. The optimal reorder points for given batch sizes in all installations were obtained from optimizing the estimated cost function. The estimation accuracy was assessed through simulation. The results indicate that the nonlinear regression model outperforms the linear one.
Maghsoud Amiri, Amir Reza Abtahi, and Kaveh Khalili Damghani
International Journal of Services and Operations Management, ISSN: 17442370, eISSN: 17442389, Pages: 355-372, Published: 2013 Inderscience Publishers
In this paper, a new mathematical formulation is proposed to model a generalised precedence multi-objective multi-mode time-cost-quality trade-off project scheduling problem (GPDTCQTP). Afterwards, a modified NSGA-II algorithm is developed to solve the proposed GPDTCQTP. The modified NSGA-II utilises a dynamic parameter tuning and a heuristic self-adaptive constraint handling strategy. These properties result in proper performance in regenerating the Pareto front of the GPDTCQTP. Investigating the efficiency of proposed algorithm several benchmark instances are systematically generated and solved. The proposed procedure is straightforward and results are promising.
A. Alimi, M. Zandieh, and M. Amiri
International Journal of Industrial Engineering Computations, ISSN: 19232926, eISSN: 19232934, Pages: 859-872, Published: 2012 Growing Science
Article history: Received 6 April 2012 Received in revised format 26 April 2012 Accepted May 24 2012 Available online 30 May 2012 Mutual fund is one of the most popular techniques for many people to invest their funds where a professional fund manager invests people's funds based on some special predefined objectives; therefore, performance evaluation of mutual funds is an important problem. This paper proposes a multi-objective portfolio optimization to offer asset allocation. The proposed model clusters mutual funds with two methods based on six characteristics including rate of return, variance, semivariance, turnover rate, Treynor index and Sharpe index. Semivariance is used as a downside risk measure. The proposed model of this paper uses fuzzy variables for return rate and semivariance. A multi-objective fuzzy mean-semivariance portfolio optimization model is implemented and fuzzy programming technique is adopted to solve the resulted problem. The proposed model of this paper has gathered the information of mutual fund traded on NASDAQ from 2007 to 2009 and Pareto optimal solutions are obtained considering different weights for objective functions. The results of asset allocation, rate of return and risk of each cluster are also determined and they are compared with the results of two clustering methods. © 2012 Growing Science Ltd. All rights reserved
Maghsoud Amiri and Ali Mohtashami
International Journal of Advanced Manufacturing Technology, ISSN: 02683768, eISSN: 14333015, Issue: 1-4, Pages: 371-383, Published: September 2012 Springer Science and Business Media LLC
This paper presents a multiobjective formulation of the buffer allocation problem in unreliable production lines. Majority of the solution methods for buffer allocation problems assume that the process times, time between failures, and repair times are deterministic or exponentially distributed. This paper relaxes these restrictions by proposing a simulation-based methodology which can consider general function distributions for all parameters of production lines. Factorial design has been used to build a meta-model for estimating production rate based on a detailed, discrete event simulation model. We use genetic algorithm combined to line search method to solve the multiobjective model and determining the optimal (or near optimal) size of each buffer storage.
Kaveh Khalili-Damghani and Maghsoud Amiri
Reliability Engineering and System Safety, ISSN: 09518320, Volume: 103, Pages: 35-44, Published: July 2012 Elsevier BV
In this paper, a procedure based on efficient epsilon-constraint method and data envelopment analysis (DEA) is proposed for solving binary-state multi-objective reliability redundancy allocation series-parallel problem (MORAP). In first module, a set of qualified non-dominated solutions on Pareto front of binary-state MORAP is generated using an efficient epsilon-constraint method. In order to test the quality of generated non-dominated solutions in this module, a multi-start partial bound enumeration algorithm is also proposed for MORAP. The performance of both procedures is compared using different metrics on well-known benchmark instance. The statistical analysis represents that not only the proposed efficient epsilon-constraint method outperform the multi-start partial bound enumeration algorithm but also it improves the founded upper bound of benchmark instance. Then, in second module, a DEA model is supplied to prune the generated non-dominated solutions of efficient epsilon-constraint method. This helps reduction of non-dominated solutions in a systematic manner and eases the decision making process for practical implementations.
Maghsoud Amiri, Nasim Ekram Nosratian, Asma Jamshidi, and Mostafa Ekhtiari
International Journal of Advanced Manufacturing Technology, ISSN: 02683768, eISSN: 14333015, Issue: 5-8, Pages: 549-558, Published: July 2012 Springer Science and Business Media LLC
Regression analysis is one of the most applicable methods in statistical methodology used to find the best regression model according to the relationship among several variables in a system. The estimation of regression model, which is solved as a formulate optimization problem and making use of heuristic algorithms, is much simpler and faster than classic methods. Genetic algorithm (GA) as one of the heuristic algorithms had been used to solve this problem. In this paper, we extend the noising method as a recent combinatorial optimization problem to estimate the best regression model and evaluate its performances compared to GA. Also, in order to enhance the performance of our GA, we apply the Taguchi experimental design method to tune the parameters of the algorithm.
S.M. Mousavi, M. Zandieh, and M. Amiri
International Journal of Production Research, ISSN: 00207543, eISSN: 1366588X, Pages: 2570-2591, Published: 15 May 2012 Informa UK Limited
This paper addresses the scheduling problems in a hybrid flowshop with two objectives of minimising the makespan and total tardiness. Since this problem is NP-hard, evolutionary algorithms based on the genetic algorithm (GA) namely; BOGAW, BOGAC, BOGAT, and BOGAS are proposed for searching the Pareto-optimal frontier. In these algorithms, we propose to generate a section of solutions for the next generation using a neighbourhood search structure on the best individual in each generation. The selection procedure selects the best chromosome based on an evaluation mechanism used in the algorithm (i.e., weighted sum, crowding distance, TOPSIS and single-objective). The aim of this paper is to clarify that the cited characteristic is efficient and it enhances the efficiency of algorithms. Therefore, we perform a comparison between the proposed algorithms to find the best alternative. Data envelopment analysis is used to evaluate the performance of approximation methods. The obtained result from the comparison ...
Maghsoud Amiri, Mostafa Ekhtiari, and Mehdi Yazdani
Expert Systems with Applications, ISSN: 09574174, Pages: 7222-7226, Published: June 2011 Elsevier BV
In problem of portfolio selection, financial Decision Makers (DMs) explain objectives and investment purposes in the frame of multi-objective mathematic problems which are more consistent with decision making realities. At present, various methods have introduced to optimize such problems. One of the optimization methods is the Compromise Programming (CP) method. Considering increasing importance of investment in financial portfolios, we propose a new method, called Nadir Compromising Programming (NCP) by expanding a CP-based method for optimization of multi-objective problems. In order to illustrate NCP performance and operational capability, we implement a case study by selecting a portfolio with 35 stock indices of Iran stock market. Results of comparing the CP method and proposed method under the same conditions indicate that NCP method results are more consistent with DM purposes.
Maghsoud Amiri and Farhaneh Golozari
International Journal of Advanced Manufacturing Technology, ISSN: 02683768, eISSN: 14333015, Issue: 1-4, Pages: 393-401, Published: April 2011 Springer Science and Business Media LLC
In this paper, we attempt to introduce an algorithm which considers not only time factor but also cost, risk, and quality criteria to determine the critical path under fuzzy environment. In this algorithm first, decision makers allocate time, cost, risk, and quality to each activity. We are lacking in data and information, so in the proposed algorithm, the ratings of each activity and the weight of each criterion are described by fuzzy numbers and linguistic variables, which can be expressed in triangular fuzzy number. Linguistic variables are applied to represent the intensity of preferences of one criterion over another. Then, we add up triangular fuzzy numbers to determine the final evaluation value of each criterion for paths. Next, we use fuzzy TOPSIS, a technique for order preferences by similarity to an ideal solution, a method proposed by the authors in another paper, to choose the best alternative. Finally, numerical example is solved to illustrate the procedure of proposed method at the end of this paper.
S. M. Mousavi, M. Zandieh, and M. Amiri
International Journal of Advanced Manufacturing Technology, ISSN: 02683768, eISSN: 14333015, Issue: 1-4, Pages: 287-307, Published: April 2011 Springer Science and Business Media LLC
This paper considers the problem of scheduling n independent jobs in hybrid flow shop environment with sequence-dependent setup times to minimize the makespan and total tardiness. For the optimization problem, an algorithm namely; bi-objective heuristic (BOH) is proposed for searching Pareto-optimal frontier. The aim of the proposed algorithm is to generate a good approximation of the set of efficient solutions. The BOH procedure initiates by generating a seed sequence. Since the output results are strongly dependent on the initial solution and in order to increase the quality of output results algorithm, we have considered how the generation of seed sequence with random way and particular sequencing rules. Two methods named Euclidean distance and percent error have been proposed to compare non-dominated solution sets obtain of each seed sequence. It is perceived from these methods that the generation of seed sequence using earliest due date rule is more effective. Then, the performance of the proposed BOH is compared with a simulated annealing proposed in the literature and a VNS heuristic on a set of test problems. The data envelopment analysis is used to evaluate the performance of approximation methods. From the results obtained, it can be seen that the proposed algorithm is efficient and effective.
M. Amiri, M. Zandieh, M. Yazdani, and A. Bagheri
International Journal of Production Research, ISSN: 00207543, eISSN: 1366588X, Pages: 5671-5689, Published: 1 October 2010 Informa UK Limited
The flexible job-shop scheduling problem (FJSP) is a generalisation of the classical job-shop scheduling problem which allows an operation of each job to be executed by any machine out of a set of available machines. FJSP consists of two sub-problems which are assigning each operation to a machine out of a set of capable machines (routing sub-problem) and sequencing the assigned operations on the machines (sequencing sub-problem). This paper proposes a variable neighbourhood search (VNS) algorithm that solves the FJSP to minimise makespan. In the process of the presented algorithm, various neighbourhood structures related to assignment and sequencing problems are used for generating neighbouring solutions. To compare our algorithm with previous ones, an extensive computational study on 181 benchmark problems has been conducted. The results obtained from the presented algorithm are quite comparable to those obtained by the best-known algorithms for FJSP.
Behnam Vahdani, Hasan Hadipour, Jamshid Salehi Sadaghiani, and Maghsoud Amiri
International Journal of Advanced Manufacturing Technology, ISSN: 02683768, eISSN: 14333015, Issue: 9-12, Pages: 1231-1239, Published: April 2010 Springer Science and Business Media LLC
Decision making is the process of finding the best option among the feasible alternatives. In classical multiple-criteria decision-making (MCDM) methods, the ratings and the weights of the criteria are known precisely. However, if decision makers cannot reach an agreement on the method of defining linguistic variables based on the fuzzy sets, the interval-valued fuzzy set theory can provide a more accurate modeling. In this paper, the interval-valued fuzzy VIKOR method is presented, aiming at solving MCDM problems in which the weights of criteria are unequal, using interval-valued fuzzy set concepts. For application and verification, this study presents a numerical example and builds a practical maintenance strategy selection problem to verify our proposed method. Moreover, a comparison is made between the interval-valued fuzzy VIKOR and other adapted MCDM interval-valued fuzzy number-based.
Saeid Fallah-Jamshidi, Maghsoud Amiri, and Neda Karimi
Applied Soft Computing Journal, ISSN: 15684946, Pages: 1274-1283, Published: September 2010 Elsevier BV
Generally the most real world production systems are tackling several different responses and the problem is optimizing these responses concurrently. This study strives to present a new two-phase hybrid genetic based metaheuristic for optimizing nonlinear continuous multi-response problems. Premature convergence and getting stuck in local optima, which makes the algorithm time consuming, are common problems dealing with genetic algorithms (GAs). So we hybridize GA with a clustering approach and particle swarm optimization algorithm (PSO) to make a balanced relationship between time consuming and premature termination. The proposed algorithm also tries to find Ideal Points (IPs) for response functions. IPs are considered as improvement measures that determine when PSO should start. PSO based local search exploit Pareto archive solutions to enhance performance of the algorithm by expanding the search space. Since there is no standard benchmark in this field, we use two case studies from distinguished paper in multi-response optimization and compare the results with some of the mentioned algorithms in the literature. Results show the outperformance of the proposed algorithm than all of them.
M. Yazdani, M. Amiri, and M. Zandieh
Expert Systems with Applications, ISSN: 09574174, Pages: 678-687, Published: January 2010 Elsevier BV
Flexible job-shop scheduling problem (FJSP) is an extension of the classical job-shop scheduling problem. FJSP is NP-hard and mainly presents two difficulties. The first one is to assign each operation to a machine out of a set of capable machines, and the second one deals with sequencing the assigned operations on the machines. This paper proposes a parallel variable neighborhood search (PVNS) algorithm that solves the FJSP to minimize makespan time. Parallelization in this algorithm is based on the application of multiple independent searches increasing the exploration in the search space. The proposed PVNS uses various neighborhood structures which carry the responsibility of making changes in assignment and sequencing of operations for generating neighboring solutions. The results obtained from the computational study have shown that the proposed algorithm is a viable and effective approach for the FJSP.
M.A. Adibi, M. Zandieh, and M. Amiri
Expert Systems with Applications, ISSN: 09574174, Pages: 282-287, Published: January 2010 Elsevier BV
Dynamic job shop scheduling that considers random job arrivals and machine breakdowns is studied in this paper. Considering an event driven policy rescheduling, is triggered in response to dynamic events by variable neighborhood search (VNS). A trained artificial neural network (ANN) updates parameters of VNS at any rescheduling point. Also, a multi-objective performance measure is applied as objective function that consists of makespan and tardiness. The proposed method is compared with some common dispatching rules that have widely used in the literature for dynamic job shop scheduling problem. Results illustrate the high effectiveness and efficiency of the proposed method in a variety of shop floor conditions.
M. Amiri, M. Zandieh, B. Vahdani, R. Soltani, and V. Roshanaei
Expert Systems with Applications, ISSN: 09574174, Pages: 509-516, Published: January 2010 Elsevier BV
The foreign exchange market (FOREX) is the largest financial market in the world, with a volume of over $2 trillion daily. Decision making about buying and selling the existing products in this market depends on several effective factors which cause the high risk in it and make it a sensitive job. So in this paper a new method which is extracted from the multiple decision making methods named eigenvector-DEA-TOPSIS methodology is presented to evaluate the risk of the number of related portfolios to this market. The eigenvector technique is used to determine the weights of criteria and some linguistic terms are applied for assessing portfolio risks under each criterion, then in order to determine the value of linguistic terms we use the data envelopment analysis (DEA) method. Finally we use TOPSIS method for aggregating portfolio risks under different criteria into an overall risk score for each portfolio and ranking the portfolios according to their risks. The integrated eigenvector-DEA-TOPSIS methodology is applicable to any number of decision alternatives and is illustrated with a numerical example.
M. Amiri, M. Zandieh, R. Soltani, and B. Vahdani
Expert Systems with Applications, ISSN: 09574174, Pages: 12314-12322, Published: December 2009 Elsevier BV
In this paper, we present a hybrid multi-criteria decision-making (MCDM) model to evaluate the competence of the firms. According to the competence-based theory reveals that firm competencies are recognized from exclusive and unique capabilities that each firm enjoy in marketplace and are tightly intertwined within different business functions throughout the company. Therefore, competence in the firm is a composite of various attributes. Among them many intangible and tangible attributes are difficult to measure. In order to overcome the issue, we invite fuzzy set theory into the measurement of performance. In this paper first we calculate the weight of each criterion through adaptive analytic hierarchy process (AHP) approach (A^3) method, and then we appraise the performance of firms via linguistic variables which are expressed as trapezoidal fuzzy numbers. In the next step we transform these fuzzy numbers into interval data by means of @a-cut. Then considering different values for @a we rank the firms through TOPSIS method with interval data. Since there are different ranks for different @a values, we apply linear assignment method to obtain final rank for alternatives.
M. Zandieh, M. Amiri, B. Vahdani, and R. Soltani
Journal of Computational and Applied Mathematics, ISSN: 03770427, Volume: 230, Pages: 463-476, Published: 15 August 2009 Elsevier BV
Most real world search and optimization problems naturally involve multiple responses. In this paper we investigate a multiple response problem within desirability function framework and try to determine values of input variables that achieve a target value for each response through three meta-heuristic algorithms such as genetic algorithm (GA), simulated annealing (SA) and tabu search (TS). Each algorithm has some parameters that need to be accurately calibrated to ensure the best performance. For this purpose, a robust calibration is applied to the parameters by means of Taguchi method. The computational results of these three algorithms are compared against each others. The superior performance of SA over TS and TS over GA is inferred from the obtained results in various situations.
Maghsoud Amiri, Farhad Ghassemi-Tari, Mohsen Rahimi Mazrae Shahi, Jamshid Salehi Sadaghiani, and Ali Mahtasshami
Journal of Applied Sciences, ISSN: 18125654, eISSN: 18125662, Pages: 1074-1081, Published: 2009 Science Alert
A. Kazemi, M. Amiri, J.S. Sadaghiani, A. Yaghoubi, and H. Mashatzadegan
Journal of Applied Sciences, ISSN: 18125654, eISSN: 18125662, Pages: 1344-1349, Published: 2009 Science Alert
S.F. Jamshidi, M. Amiri, and N. Karimi
Journal of Applied Sciences, ISSN: 18125654, eISSN: 18125662, Pages: 3199-3206, Published: 2008 Science Alert
Amir Abbas Najafi, Maghsoud Amiri, and Komeil Gheshlaghi
Journal of Applied Sciences, ISSN: 18125654, eISSN: 18125662, Pages: 2732-2738, Published: 2008 Science Alert
M. Amiri, B. Hadadi, A.H. Amirkhani, and H. Izadbakhsh
Journal of Applied Sciences, ISSN: 18125654, eISSN: 18125662, Pages: 3715-3720, Published: 2008 Science Alert
M. Amiri, F. Ghassemi-Tari, A. Mohtashami, and J.S. Sadaghiani
Journal of Applied Sciences, ISSN: 18125654, eISSN: 18125662, Pages: 4105-4112, Published: 2008 Science Alert
A. Kazemi, M. Amiri, N.E. Nosratian, and A. Jamshidi
Journal of Applied Sciences, ISSN: 18125654, eISSN: 18125662, Pages: 4017-4028, Published: 2008 Science Alert
A. Kazemi, M. Amiri, H. Hadipour, and R. Azizmohammadi
Journal of Applied Sciences, ISSN: 18125654, eISSN: 18125662, Pages: 4390-4396, Published: 2008 Science Alert
M. Zandieh, M. Amiri, B. Vahdani, M. Yazdani, and R. Soltani
Journal of Applied Sciences, ISSN: 18125654, eISSN: 18125662, Pages: 2678-2686, Published: 2008 Science Alert
Scientia Iranica, ISSN: 10263098, Pages: 389-397, Published: May/June 2008
Maghsoud Amiri and Farhad Ghassemi-Tari
Applied Mathematics and Computation, ISSN: 00963003, Volume: 184, Pages: 300-307, Published: 15 January 2007 Elsevier BV
In this paper we present a method for transient analysis of availability and survivability of a system with the identical components and identical repairmen. The considered system is supposed to consist of series of k-out-of-n or parallel components. We employed the Markov models, eigen vectors and eigenvalues for analyzing the transient availability and survivability of the system. The method is implemented through an algorithm which is tested in MATLAB programming environment. The new method enjoys a stronger mathematical foundation and more flexibility for analyzing the transient availability and survivability of the system.
Scientia Iranica, ISSN: 10263098, Pages: 72-77, Published: January/February 2007