The multi-objective competitive location problem for congested systems

In this paper, we introduce a multi-objective competitive location model for congested systems considering probabilistic-choice behavior and existing competitors in the market. The user-choice behavior is considered based on gravity function that depends on both quality/reputation of service provider and the traveling time to facility. Since the derived model belongs to NP-hard multi-objective optimization problems, thus two multi-objective genetic algorithms are proposed to solve the model. In order to evaluate the performance of two multi-objective genetic algorithms we compared the average number of Pareto-optimal solutions and run time of each algorithm. Computational results show the performance of the solution methods is reasonable