Integrating environmental, social and risk factors in lot-sizing and supply chain network design
提出了一个混合整数模型，同时解决批量确定和供应链网络设计问题，整合了可持续性、风险、库存管理和碳足迹，帮助管理者在考虑多周期、多层级结构下做出最优决策。
In today’s world, supply chains are expected to be better equipped to deal with sustainability issues and risks while making appropriate business decisions. In particular, the ordering policy and the design of the supply chain network (SCND) significantly contribute to the sustainability dimensions and mitigate organisational risks. Traditionally, models that determine ordering decisions (such as capacitated lot size (CLS)) and SCND problems are considered in isolation. To date, there is no model that addresses both these problems in an integrated manner under consideration of all three sustainability dimensions, risk dimensions, inventory management, and carbon footprint. To fill the existing literature gaps, the proposed study introduces a mixed-integer model that integrates CLS and SCND challenges, accounting for practical concerns like multi-period dynamics, multi-echelon structures, sustainability impacts, risk mitigation, and inventory management. This model supports crucial decisions, such as determining the optimal supply network (including the location of manufacturing units and warehouses) and calculating material flow across various supply chain network periods. The modelling approach includes: (i) assessing suppliers’ risk and social scores using Best–Worst Method (BWM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) techniques; (ii) incorporating these scores into the model; and (iii) utilising a Lagrangian relaxation (LR) heuristic to solve the integrated model. The applicability and validity of the proposed model have been examined using a numerical case study, and sensitivity analyses have been performed to understand the robustness of the proposed modelling approach. The performance of the proposed approach was compared with that of existing solution methodologies in terms of computational efficiency and the quality of the solution obtained. The Lagrangian-based integrated model yields a smaller gap percentage (0.4%), indicating the effectiveness and accuracy of the model. The proposed model can help practitioners and managers make efficient and effective decisions when solving joint CLS-SCND problems, addressing challenging issues related to sustainability and risk.