Optimizing localized humanitarian logistics: a stochastic programming approach for facility location, inventory and evacuation strategies

Purpose Humanitarian logistics is vital for effective disaster response and preparedness, particularly in flood-prone regions where rapid and efficient relief operations can mitigate severe socioeconomic impacts. This paper aims to present a multi-objective two-stage stochastic optimization model designed to enhance humanitarian logistics and supply chain management by integrating facility location, inventory management, evacuation planning and vehicle logistics. The study aims to optimize response time, budget allocation and evacuation efficiency while addressing uncertainties in disaster scenarios. Design/methodology/approach The proposed model incorporates probabilistic disaster scenarios derived from flood hazard maps in Cambodia to simulate real-world uncertainties and improve decision-making. A stochastic programming approach balances multiple objectives to ensure efficient resource allocation. The weighted sum method is used to solve the multi-objective optimization problem, allowing decision-makers to analyze trade-offs between different performance metrics. A sensitivity analysis evaluates the impact of warehouse utilization rates on response times and costs, providing valuable insights for adaptive and cost-effective disaster planning strategies. In addition, trade-off analysis using the AUGMECON method provides decision-makers with a spectrum of Pareto-efficient solutions each offering different balances between speed, cost and reach. Findings The proposed model demonstrates significant improvements over traditional humanitarian logistics frameworks, achieving a 63.17% reduction in response time, 30.32% lower budget allocation and a 43.41% decrease in evacuation distances. The findings emphasize the importance of localized disaster management strategies, leveraging local markets, warehouses and shelters to enhance resilience and reduce dependence on external aid. Originality/value This research introduces a novel optimization framework that integrates local resource utilization into humanitarian logistics, improving sustainability and adaptability. The findings provide practical insights for policymakers and humanitarian organizations, supporting the development of cost-effective, scalable and adaptive disaster response strategies.