Robust Optimization for the Location Selection of Emergency Life Supplies Distribution Centers Based on Demand Information Uncertainty: A Case Study of Setting Transfer Points

Following various natural and man-made disasters, a critical challenge in emergency response is establishing an emergency living supplies distribution center that minimizes service costs while ensuring rapid and efficient delivery of essential goods to affected populations, thereby safeguarding their lives and material well-being. The study addresses this challenge by developing an optimization function to minimize the total service cost for locating such distribution centers, using connection points as a foundation. Utilizing a robust optimization approach that incorporates constraint conditions and bounded intervals as the value set for uncertain demand, the optimization function is transformed into a robust equivalent model through the dual principle. The tabu search method, integrated with MATLAB R2015b software, is employed to perform statistical analysis on the data, yielding the optimal solution. Case study analysis demonstrates that the minimum total service cost escalates with increases in robustness level and disturbance parameters. Furthermore, the model incorporating connection points consistently yields better results than the model without connection points, highlighting the efficacy of the proposed approach.