The Optimization Of Facility Location And Allocation For Emergency Rescue: A Case Study Of Hue Province

Abstract

The study addresses the critical need for effective emergency response planning in the most disaster-prone region in Vietnam which is Hue Province, emphasizing the strategic placement of emergency warehouses in order to optimize operational costs. The approach involves two phases: (1) identifying optimal warehouse locations and (2) allocating resources effectively to mitigate the impact of disasters. Hence, we propose some methodologies including mathematical model and the implementation of Two stage Stochastic Programming (TSP), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA). The objective is to improve emergency management preparedness by maximizing responsiveness and distribution efficiency. As a result, the outcomes of validation and sensitivity testing reveal that TSP delivers the most optimal results in small datasets, PSO excels in rapid solution search, and GA provides stable solutions for large-scale data in crisis scenarios. However, many challenges such as computational complexity and limited data availability in remote areas highlight the necessity for future research to enhance scalability and real-time adaptability.