An Adaptive Parameter Control Strategy for Ant Colony Optimization

Abstract

proved to be one of the best performing algorithms for NP-hard combinational optimization problems like TSP. Many researchers have been attracted in research for ACO but fewer tuning methodologies have been done on its parameters which influence the algorithm directly. The setting of ACO's parameters is studied in this paper. The Artificial Fish Swarm Algorithm (AFSA) is introduced to solve the parameter tuning problem, and an adaptive parameter setting strategy is proposed. It's proved to be effective by the experiment based on TSPLIB test. Keywords: Artificial Fish Swarm Algorithm, Ant Colony Optimization, parameters, TSP