An Adaptive Parameter Control Strategy for ACO

Ant colony optimization (ACO) has been proved to be one of the best performing algorithms for NP-hard problems as TSP. Many strategies for ACO have been studied, but fewer tuning methodologies have been done on ACO´s parameters which influence the algorithm directly. The setting of ACO´s parameters is considered as a combinational optimization problem in this paper. The particle swarm optimization (PSO) is introduced to solve this problem, and an adaptive parameter setting strategy is proposed. It´s proved to be effective by the experiment based on TSPLIB test