An improved discrete particle swarm optimization algorithm for the capacitated p-median problem

Abstract

Capacitated p-median problem (CPMP) is a kind of location problem which belongs to combinatorial optimization problem. In this paper, an improved discrete particle swarm optimization (IDPSO) algorithm is present to solve the CPMP. In the IDPSO, the candidate particle is affected by the particle local best location (it is called as pBest) and global best position (it is called as gBest) through performing crossover operation with them; while inertia effect is considered as mutation operation. In order to further adjust median points' position, cluster idea is introduced. Secondly, some key issues, such as the particle representation, particle initial process, particle update, fitness evaluation are addressed. And then, two local search operators are applied to refine the particle; and the particle replace strategy based on simulated annealing method is used to keep the diversity of the particles. The results of the experiment show that proposed algorithm could perform well while comparing with other heuristic algorithms.