| dc.description.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. | en_US |
