Large-scale group decision making for simulation-guided disaster recovery center location selection

Abstract

Given the potential severe impact of supply chain disruptions on production capacity and delivery times, such disruptions represent a significant risk for manufacturing enterprises. In this context, it is crucial to enhance the resilience of the supply chain and ensure business continuity during crises. This paper introduces a novel simulation-driven model that identifies the best locations for disaster recovery centers (DRCs) to reduce these risks. Using the anyLogistix software, we simulate an enterprise supply chain and evaluate potential DRC locations based on six key characteristics that were derived from a comprehensive literature review. Then, to evaluate these places and find the best DRC site, decision-makers combined large-scale group decision-making (LSGDM) with improved interval-valued two-tuple linguistic evaluation. anyLogistix simulation confirms the effectiveness of the selected DRCs in mitigating distribution center disruptions, providing crucial management guidance. The innovative integration of LSGDM and simulation demonstrates that establishing DRCs significantly reduces the negative impacts of supply chain disruptions. Comparative analyses validate the model’s rationality and feasibility, offering a valuable framework for enhancing supply chain resilience in manufacturing enterprises. This research contributes to the field by presenting a comprehensive approach to DRC location selection that considers both quantitative and qualitative factors and highlights the importance of proactive risk management strategies in ensuring the continuity of manufacturing supply chains.