Multi-colony ant optimization with dynamic collaborative mechanism and cooperative game

Abstract Ant Colony Optimization easily falls into premature stagnation when solving large-scale Travelling Salesmen Problems. To address this problem, a multi-colony ant optimization with dynamic collaborative mechanism and cooperative game is proposed. Firstly, System Max–Min form heterogeneous colonies. Secondly, to diversify the solutions of algorithm, Shapley value in applied share information by distributing pheromone payoff sub-colonies. In addition, that contains two methods designed enhance co-evolution populations. One, called public path recommendation strategy, proposed improve astringency . The other fusion regulate distribution algorithm stagnation, which can help jump out local extremum effectively. Finally, results demonstrate methodology accuracy solution effectively TSP instances has strong competitiveness swarm intelligent algorithms.