A PARETO-BASED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR MULTI-OBJECTIVE LOCATION ROUTING PROBLEM

This paper deals with multi-objective location routing problem. The two conflicting objectives considered are to minimize total cost and to maximize total customer demand served. The multi-objective particle swarm optimization algorithm is applied to solve this problem by searching for the Pareto front. A specific solution representation is adopted and two different decoding methods are designed for multi-objective location routing problem. The test problem instances used to evaluate the algorithm are modified from previously published test problem instances for single objective location routing problem. The experimental results demonstrated that the proposed algorithm can effectively provide good Pareto fronts for most test problem instances by both decoding methods but with different solution quality.