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An Adaptive Parameter Control Strategy for Ant Colony Optimization

机译:蚁群优化的自适应参数控制策略

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摘要

Ant Colony Optimization (ACO) has been 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.
机译:蚁群算法(ACO)被证明是解决NP-hard组合优化问题(例如TSP)的最佳算法之一。许多研究人员都对ACO进行了研究,但对其参数的影响方法的调优方法却很少本文直接研究了ACO的参数设置。引入人工鱼群算法(AFSA)解决了参数调整问题,提出了一种自适应参数设置策略,通过基于TSPLIB的实验证明是有效的。测试。

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