An Exploration of Evolutionary Algorithms for a Bi-objective Competitive Facility Location Problem in Congested Systems

Abstract

This paper presents a bi-objective competitive facility location model for congested systems in which entering facilities will compete with the competitors' facilities for capturing the market share. In the proposed model, customers can chose which facility to patronize based on the gravity function that depends on both the quality of service provider and the travel time to facilities. The proposed model attempts to simultaneously maximize the captured demand by each facility and minimize the total waiting times at the system. To solve the model, two multi-objective evolutionary algorithms, involving a multi-objective harmony search algorithm (MOHS) and a non-dominated sorting genetic algorithm-II (NSGA-II), are proposed. The performance of solution procedures are compared in terms of different performance metrics including generational distance, spacing metric, diversification metric, and number of non-dominated solution. Computational results based on different problem sizes show that in general MOHS outperforms NSGA-II.