A multi-objective location analytics model for temporary emergency service center location decisions in disasters

This study presents a real-world multi-objective facility location analytics model for determining the number and locations of Temporary Emergency Service Centers (TESCs) for a regional natural gas distribution company in Turkey. These centers are set up temporarily after natural disasters (i.e., earthquakes, floods, storms) in response to emergencies like gas leaks and distribution problems. The proposed model considers three objectives, including p-median, maximal coverage, and p-center to minimize average and maximum transfer time while accommodating as many victims as possible within predetermined ranges. The proposed method uses the ITER-FLOC (Iterative Facility Location) algorithm to solve the TESC location problem. The proposed model employs an integrated and iterative branch and bound algorithm with goal programming. The solution approach provides decision-makers with a set of Pareto optimal solutions and a unique compromise solution for all objectives incorporated in the decision analytics model.