Maghsoud Amiri
@atu.ac.ir
Department of Industrial Management, Faculty of Management and Accounting
Allameh Tabataba’i University
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Seyyed Jalaladdin Hosseini Dehshiri, Maghsoud Amiri, Ali Mostafaeipour, and Ttu Le
Elsevier BV
Seyyed Jalaladdin Hosseini Dehshiri and Maghsoud Amiri
Elsevier BV
Seyyed Jalaladdin Hosseini Dehshiri, Maghsoud Amiri, and Seyed Mojtaba Hosseini Bamakan
Elsevier BV
Saeed Sadeghi Darvazeh, Farzaneh Mansoori Mooseloo, Fatemeh Gholian-Jouybari, Maghsoud Amiri, Hossein Bonakdari, and Mostafa Hajiaghaei-Keshteli
Elsevier BV
Parisa Alizadeh and Maghsoud Amiri
Emerald
Purpose Business research and development (R&D) is of critical importance for innovation and economic growth. The purpose of this study is to present an application of the analytic hierarchy process (AHP) to select the most appropriate policy measure to support the business expenditure on R&D (BERD). Design/methodology/approach AHP method adopts a multi-criteria approach that can be used to analyse and prioritize the policy measures based on pairwise comparisons between several attributes that affect the selection of a policy tool. The model formulated in this study is applied to a real case of supporting decision-makers in some high-tech sectors in Iran. Findings The results highlight the four main financial policy measures implemented in Iran to enhance the BERD; those are, public procurement for R&D, direct subsidies for R&D, grants for R&D and income tax credit for firms have the priority values of 0.280, 0.260, 0.249 and 0.211, respectively. Research limitations/implications The findings of this study are based on subjective evaluation of policy measures by experts of designing policy measures. Objective assessment of policy measures is important too because the preferences of policy interventions change during the time. Another significant point is that the priorities of specific policy measures depend on the effectiveness of their implementing arrangement and the previously successful experience of firms in receiving them. Originality/value This paper presents an application of the AHP to select the most appropriate policy measure to support the BERD. This method could be used to prioritize the policies and interventions that governments implement to solve different problems, especially at the innovation system level.
Seyed Alireza Seyed Haeri, Maghsoud Amiri, S.M. Ali Khatami Firouzabadi, Kaveh Khalili-Damghani, and Mani Sharifi
Elsevier BV
Mehrnoosh Zohrehvandi, Shakib Zohrehvandi, Mohammad Khalilzadeh, Maghsoud Amiri, Fariborz Jolai, Edmundas Kazimieras Zavadskas, and Jurgita Antucheviciene
MDPI AG
The aim of this study was to develop a multi-objective mathematical programming model for the trade-off of time, cost, and quality in the project-scheduling problem (PSP) by taking priorities and resource constraints as well as activity preemption into account. First, a small-sized problem instance that was a sub-project of an oil and gas construction project was used for te validation of the proposed model and algorithm. Subsequently, considering the sensitivity, complexity, and importance of oil and gas projects, the proposed model was implemented in a large-sized oil and gas construction project. Considering the NP-hardness of this problem, the NSGA-II metaheuristic algorithm was used to deal with the time, cost, and quality trade-off problem. Finally, a sensitivity analysis was implemented on the three main parameters of time, cost, and quality to investigate the effects of changes on the results. The findings show that the proposed model is more sensitive to cost changes, so an increase in project costs leads to a drastic change in the values of other objective functions.
Seyyed Jalaladdin Hosseini Dehshiri and Maghsoud Amiri
Elsevier BV
Seyyed Jalaladdin Hosseini Dehshiri and Maghsoud Amiri
Elsevier BV
Seyyed Jalaladdin Hosseini Dehshiri, Ahmad Yousefi Hanoomarvar, and Maghsoud Amiri
Springer Science and Business Media LLC
Mir Seyed Mohammad Mohsen Emamat, Saif Wakeel, Maghsoud Amiri, Shafi Ahmad, and Sedat Bingol
Springer Science and Business Media LLC
Hamze Pourbabagol, Maghsoud Amiri, Mohammad Taghi Taghavifard, and Payam Hanafizadeh
Elsevier BV
Maghsoud Amiri, Mohammad Hashemi-Tabatabaei, Mehdi Keshavarz-Ghorabaee, Jurgita Antucheviciene, Jonas Šaparauskas, and Mohsen Keramatpanah
MDPI AG
Modern technologies have changed human life and created a generation of customers who have different needs compared to the past. Considering Industry 4.0 and its drivers, the implementation of digital banking (DB) has faced various challenges that are caused by emerging trends. Both Industry 4.0 and DB are contemporary concepts, and decision-makers are often faced with uncertainties in their decisions regarding the implementation of DB and its indicators. For this purpose, a novel multi-criteria group decision-making approach has been developed utilizing the best–worst method (BWM) and α-cut analysis as well as trapezoidal fuzzy numbers (TFNs). By reviewing the literature and using experts’ opinions, the DB implementation criteria are determined, and considering an uncertain environment, the criteria are prioritized using the proposed method. Then, the available DB models and alternatives are examined based on the decision criteria and the importance of each criterion. This research contributes to the existing literature by identifying and prioritizing the criteria necessary for the successful implementation of DB, taking into account emerging trends and technological advances driven by Industry 4.0. Subsequently, the study prioritizes the prevalent models of DB based on these criteria. This study proposes a decision-support framework for dealing with ambiguity, lack of information, insufficient knowledge, and uncertainty in decision-making. The framework uses TFNs to account for imprecision and doubt in decision-makers’ preferences. Additionally, the study presents a fuzzy multi-criteria group decision-making approach that enables a group of experts to arrive at more reliable results. The proposed approach can help improve the quality of decision-making in complex and uncertain situations. The results of this research show that human resources, rules and regulations, and customer satisfaction are the most important criteria for implementing DB. In addition, the open, blockchain, and social banking models are the crucial models that significantly cover the implementation criteria for DB.
A. Mojaver Tabrizi, Behnam Vahdani, F. Etebari, and M. Amiri
Elsevier BV
Mina Dehghani Jeshvaghani, Maghsoud Amiri, Kaveh Khalili-Damghani, and Laya Olfat
Elsevier BV
Seyyed Jalaladdin Hosseini Dehshiri and Maghsoud Amiri
Springer Science and Business Media LLC
Mir Seyed Mohammad Mohsen Emamat, M. Amiri, Mohammad Reza Mehregan and Mohammad Taghi Taghavifard
Seyyed Jalaladdin Hosseini Dehshiri, Maghsoud Amiri, Laya Olfat, and Mir Saman Pishvaee
Elsevier BV
Saeid Sadeghi Darvazeh, Maghsoud Amiri, Farzaneh Mansouri Musolu, Masoomeh Sadeghi, Yaser Goldust, and Sara Moslemi
Inderscience Publishers
Farjam Kayedpour, Maghsoud Amiri, Mahmoud Rafizadeh, Arash Shahryai Nia, and Mani Sharifi
SAGE Publications
Many studies have been conducted on designing systems based on the redundancy allocation problem (RAP). However, considering repairable warm-standby components (which are subject to failure even in an idle state) is somewhat neglected by researchers due to the complex mathematical models. One of the crucial aspects of these systems is considering the probability of failure when switching to a standby component or subsystem. This study tries to highlight these imperfect switching and switch selection strategies in the redundancy allocation designs. In this regard, this article is dedicated to developing two RAP models (a single objective and a bi-objective) with warm standby repairable components by proposing a solving approach based on the genetic algorithm (GA) and Markov chains. Since the model’s objective functions minimize the system’s mean time to failure (MTTF) and cost, we discussed how imperfect switches affect the total system’s cost and mean time to failure for the proposed RAPs. Finally, we adopted a GA and a non-dominated sorting genetic algorithm (NSGA-II) to solve the proposed models due to the models’ complexity. Solving these models clearly indicates the critical role of selecting an appropriate switching strategy on the system’s costs and reliability.
Azadeh Salami, Behrouz Afshar-Nadjafi, and Maghsoud Amiri
Frontiers Media SA
Objective: This study assesses a multi-period capacitated maximal-covering location-allocation model for healthcare services, taking interservice referral as well as equity access into account.Methods: A two-stage optimization strategy is used to formulate the model. In the first stage, facilities are located to maximize covered demand, and in the second stage, patients are allocated to capacitated facilities based on their radius of coverage over multiple time periods. The problem, which belongs to the NP-hard class of optimization problems, is solved using a linear mixed-integer programming (MILP) model.Results: A numerical example is presented to evaluate the efficiency of the proposed model. In addition, to identify near-optimal solutions for large instances, a hybrid genetic-sequential quadratic programming approach (GA-SQP) is developed. To examine the performance and efficiency of the GA-SQP, we employed several randomly generated test instances of various sizes and compared them to those obtained using the exact method.Conclusion: The proposed model has demonstrated an excellent ability in locating healthcare facilities and allocating health services while taking shortage and equity into account during each time period.
Maghsoud Amiri, Mohammad Hashemi-Tabatabaei, Mehdi Keshavarz-Ghorabaee, Arturas Kaklauskas, Edmundas Kazimieras Zavadskas, and Jurgita Antucheviciene
MDPI AG
Today, most of the issues and challenges faced by managers and decision makers are complex and multifaceted. More clearly, due to the developments of technologies, emerging trends in various industries, competitive markets, and rapid and transformative changes in the business environment, managers and decision makers have faced an uncertain environments and issues that cannot be resolved definitively. The use of multi-criteria decision-making (MCDM) methods as a practical and decision-supporting tool allows managers to examine decision-making issues in various organizations and industries based on various criteria, alternatives, and objectives and make decisions with greater reliability. The use of fuzzy techniques and concepts in MCDM methods and their mathematical relationships makes it possible to consider complexities and uncertainties in decisions related to various issues and it can lead to better and more realistic decisions. In this paper, the simplified best-worst method (SBWM), which is one of the methods based on pairwise comparisons, has been developed using triangular fuzzy numbers (TFNs) to propose a fuzzy extension of SBWM (F-SBWM). Triangular fuzzy numbers in different symmetric and asymmetric forms have widely been used in MCDM approaches and pairwise comparisons. It is noteworthy that symmetric numbers are used when we are using equal division of the domain due to an increased ambiguity and lack of information. The proposed approach as a simplified fuzzy MCDM method helps managers and decision makers in various industries to solve decision-making problems under uncertainty without the need for complex calculations, specialized skills, and software packages. To check the feasibility and applicability of the proposed approach, two numerical examples and a computational experiment with real data are presented, and the results are analyzed and discussed. Furthermore, to check the robustness of the results obtained from the proposed approach, sensitivity analysis and comparison of methods have been performed.
Shakib Zohrehvandi, Mario Vanhoucke, Mohammad Khalilzadeh, Maghsoud Amiri, and Shahram Shadrokh
Informa UK Limited
Mehdi Keshavarz-Ghorabaee, Maghsoud Amiri, Edmundas Kazimieras Zavadskas, Zenonas Turskis, and Jurgita Antuchevičienė
Vilnius Gediminas Technical University
Studies related to transportation planning and development have been in the center of activities of many researchers in the past decades. Road congestions issues, economic problems, health problems and environmental problems are some examples of complex problems that can be caused by urban and public transportation in big cities. Evaluating urban and public transportation systems could help to reach effective solutions to overcome these issues. This article presents a short bibliographic review of some recent studies on Multi-Criteria Decision-Making (MCDM) approaches for evaluating urban and public transportation systems. To this aim, Scopus was chosen as the database for making a search on journal articles. Scopus is trusted by major institutions in the world, and all journals covered in this database are inspected for sufficiently high quality each year. The search was made on the journal articles from 2017 to 2022 (July). The analyses presented in this study show that the Analytic Hierarchy Process (AHP) method is the most used method, which has been applied to different studies in the field of urban and public transportation systems based on MCDM approaches. According to the analysis of the number of articles, Turkey is ranked 1st among different countries, and “Budapest University of Technology and Economics” (Hungary) is 1st in the ranking of institutions. Moreover, most of the articles have been published within the “social sciences” subject area. The recent trend in different studies on urban and public transportation systems shows the importance of using MCDM approaches in this field. Moreover, noticeable employment of fuzzy sets in several studies is a point that can shows the significant role of uncertainty in dealing with this type of problems.