Sustainable post-disaster humanitarian logistics network design: A real-case study with consecutive disaster risks

Abstract

Humanitarian logistics involves managing assets, skills, and knowledge to provide emergency relief to vulnerable societies against disasters and emergencies. After disasters, it is essential to mobilize logistics resources to assist victims and transport humanitarian supplies. An efficient and sustainable aid response plan can decrease social, economic, and environmental impacts. This paper dwells on sustainable post-disaster humanitarian logistics (SPD-HL) with environmentally friendly and conventional vehicles. The problem aims to establish the routes, schedules, and charges of the heterogeneous fleet, which designs the distribution of multi-relief items to vulnerable people in emergency assembly points and temporary shelter areas spread out in a geographically dispersed area. The objective of the SPD-HL is to minimize the total time that covers total travel time, charging duration, and total earliness and lateness. To solve this new complicated problem variation, we developed a sophisticated metaheuristic that integrates an adaptive large neighborhood search (ALNS) with a problem-specific construction and local search procedures. We conducted extensive experimental analyses on new real-world data instances to examine the performance of the heuristic. According to computational results, the proposed method effectively yields high-quality solutions compared to CPLEX results in small-size instances and improves solution quality in large-size instances. Additionally, we conduct scenario analyses with an energy and social cost-based combined objective function and the probability of road closure cases due to consecutive disasters. The results can aid decision-makers in designing an efficient, sustainable emergency logistics network in the aftermath of disasters in a reasonable time to lessen the loss of human life, costs, and environmental impact.