Joaquim Jorge da Costa Máximo Vicente

@isg.pt

CEG-IST Centre for Management Studies, Instituto Superior Técnico
Instituto Superior de Gestão (ISG-Business & Economics School)

Joaquim Jorge da Costa Máximo Vicente


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https://researchid.co/q-5845-2017

RESEARCH INTERESTS

Supply Chain Management
Operations Management
Logistics Management
13

Scopus Publications

Scopus Publications

  • Towards Sustainable Inventory Systems: Multi-Objective Optimisation of Economic Cost and CO2 Emissions in Multi-Echelon Supply Chains
    Joaquim Jorge Vicente
    Sustainability Switzerland, 2026
    Effective supply chain planning increasingly requires balancing cost-efficiency with environmental responsibility, particularly as organisations face growing pressure to reduce the carbon footprint of logistics operations. This study develops a mixed-integer linear programming model to optimise inventory and transportation decisions in a multi-echelon distribution network comprising a central warehouse, regional warehouses, and retailers. The model integrates a continuous-review (r,Q) replenishment policy, stochastic demand, safety stock requirements, transportation lead times, and stockout behaviour, enabling a detailed representation of operational dynamics under uncertainty and environmental concerns. Unlike most sustainable inventory models—which typically treat environmental impacts and replenishment control separately or rely on simplified service assumptions—this study provides an integrated framework that jointly embeds (r,Q) policies, stochastic demand, stockouts and distance-based CO2 metrics within a unified optimisation structure. The model advances prior work by explicitly integrating continuous-review (r,Q) replenishment policies with distance-based CO2 metrics under stochastic demand, a combination rarely addressed in sustainable multi-echelon inventory models. A multi-objective formulation captures the trade-off between economic performance and CO2 emissions, allowing the identification of Pareto-efficient strategies that reconcile financial and environmental goals. Reducing emissions by over 90% requires an additional cost of only about 4%, demonstrating that substantial emission reductions can be achieved at relatively low additional cost. The findings offer practical insights for managers seeking to design more sustainable and cost-effective distribution policies, highlighting the value of integrated optimisation approaches in contemporary logistics systems.
  • Dual goals, one fleet: an optimization model for balancing cost-emission trade-offs when planning mixed bus fleets
    Teresa Cardoso-Grilo, Sofia Kalakou, Joaquim Jorge Vicente
    International Journal of Systems Science Operations and Logistics, 2026
  • Impact of Container Reverse Logistics on the Maritime Sector: Economic and Environmental Factors
    Joaquim Jorge Vicente, Lurdes Neves, Catarina Marques
    Logistics, 2025
    This paper investigates the growing problem of abandoned maritime containers and the lack of effective reverse logistics to manage them: Background: The research highlights the significant environmental impact and economic burdens caused by the imbalance of container inflow and outflow, which leads to the accumulation of containers in storage yards; Methods: The study used the Delphi Method, gathering insights from a panel of experts in container transport and maintenance. The goal was to identify key challenges and potential solutions for improving container reverse logistics in Portugal; Results: The results confirm the urgent need for efficient reverse logistics strategies to address the container imbalance. The experts reached over 60% consensus on the importance of developing logistics systems and improving communication between ports. Implementing these strategies would not only reduce economic costs but also significantly lower environmental pollution; Conclusions: The paper concludes that a strategic shift toward effective reverse logistics is essential for enhancing the sustainability and operational efficiency of the maritime transport sector.
  • Optimizing Supply Chain Inventory: A Mixed Integer Linear Programming Approach
    Joaquim Jorge Vicente
    Systems, 2025
    Inventory supply chain planning involves determining the quantity of products to be transported among entities within a specified planning horizon. Often, inventory levels are reviewed at set intervals: (1) Background: In this paper, periodic review (s,S) policy is used to optimize inventories from an integrated perspective of inventory management across the supply chain. The decision to place an order and the order quantity are based on the inventory level at the review time. If the inventory falls below a certain level (s), an order is placed to replenish it to a target level (S); (2) Methods: The planning model is implemented using a mixed integer linear programming model. It determines the inventory levels, supply levels and the (s) and (S) levels for each entity, as well as the flow of products between them. To test the model, a case study is conducted to demonstrate its applicability; (3) Results: The experimental data confirm the model’s validity, as its behavior aligns with the expectations for a periodic review (s,S) policy; (4) Conclusions: Since a fixed replenishment frequency is mandatory, with no continuous inventory review required, this policy offers simplicity and ease of implementation, making it a practical choice for certain inventory management.
  • Cost-Effective and Operationally Sustainable Supply Chain Inventory Planning: A Mathematical Programming Approach
    Joaquim Jorge Vicente, Teresa Cardoso-Grilo
    Smart Innovation Systems and Technologies, 2025
  • Optimizing inventory planning in multi-echelon supply chains under uncertainty: a decision-making approach using review policies
    Joaquim Jorge Vicente, Susana Relvas, Ana Paula Barbosa-Póvoa
    International Journal of Management Science and Engineering Management, 2025
  • The potential of Logistics 4.0 technologies: a case study through business intelligence framing by applying the Delphi method
    Joaquim Jorge Vicente, Lurdes Neves, Inês Bernardo
    Frontiers in Artificial Intelligence, 2024
    IntroductionThe growing competitiveness and the importance of data availability for organizations have created a demand for intelligent information systems capable of analyzing data to support strategy and decision-making. Organizations are generating more and more data due to new technologies associated with Industry 4.0 and Logistics 4.0, making it essential to transform this data into relevant information to streamline decision-making processes. This paper examines the influence of these technologies on gaining a competitive advantage, specifically in a logistics company, which is scarce in the literature.MethodsA case study was conducted in a Portuguese company using the Delphi method with 61 participants—employees who use the company’s integrated BI tool daily. The participants were presented with a questionnaire via the online platform Welphi, requiring qualitative responses to various statements based on the literature review and the results of semi-structured meetings with the company.ResultsThe study aimed to identify areas where employees believe more investment/ development is needed to optimize processes and improve the use of the BI tool in the future. The results indicate that BI is a crucial technology when aligned with a company’s objectives and needs, highlighting the necessity of top management’s involvement in optimizing the BI tool. Encouraging employees to use the BI tool emerged as a significant factor, underscoring the importance of leadership in innovative projects to achieve greater competitive advantage for the company.DiscussionThis study aims to understand the importance of Business Intelligence (BI) and how its functionalities should be adapted according to a company’s strategy and objectives to optimize decision-making processes. Thereby, the discussion focused on the essential role of BI technologies in leveraging the company’s competitive advantage.
  • Distribution and inventory planning in multi-echelon supply chains under demand uncertainty
    Ana Barbosa Póvoa, Susana Relvas, Joaquim Jorge Vicente
    International Journal of Operational Research, 2023
  • Supply chain management under product demand and lead time uncertainty
    Joaquim Jorge Vicente, Susana Relvas, Ana Paula Barbosa Póvoa
    International Journal of Operational Research, 2020
  • Effective bullwhip metrics for multi-echelon distribution systems under order batching policies with cyclic demand
    Joaquim Jorge Vicente, Susana Relvas, Ana Paula Barbosa-Póvoa
    International Journal of Production Research, 2018
    A large number of problems in a distribution supply chain require that decisions are made in the presence of the bullwhip effect phenomenon. The impact of the order batching policies on the bullwhip effect is analysed in this paper, when cycle demand on a multi-echelon supply chain operating is considered. While investigating which bullwhip effect metrics are more adequate to measure the bullwhip effect in these type of systems, the optimal reordering plan that minimises the operation costs of the overall system is calculated. A Mixed Integer Linear Programming (MILP) model is developed that takes into account an inventory and distribution system formed by multiple warehouses and retailers with lateral transshipments. The bullwhip effect is measured through four metrics: the echelon average inventory; the echelon inventory variance ratio; the echelon average order; and the echelon order rate variance ratio. As conclusion the inventory metrics suggest that (i) using batching policy reduces instability; (ii) batching may reduce in general order variance if using larger batches and (iii) cycle demand length has no major impact in the bullwhip effect. A motivational example and a real word case study are used and tested.
  • Bullwhip effect metrics for multi-echelon systems under order batching policies with cyclic demand
    Joaquim Jorge Vicente, Susana Relvas, Ana Paula Barbosa-Povoa
    Proceedings of 2015 International Conference on Industrial Engineering and Systems Management IEEE Iesm 2015, 2016
  • Distribution supply chain inventory planning under uncertainty
    Operations Research and Big Data Io2015 Xvii Congress of Portuguese Association of Operational Research Apdio, 2015
  • Distribution Supply Chain Inventory Planning under Uncertainty
    Joaquim Jorge Vicente, Susana Relvas, Ana Paula Barbosa-Póvoa
    Studies in Big Data, 2015