计算机科学 ›› 2014, Vol. 41 ›› Issue (12): 151-154.doi: 10.11896/j.issn.1002-137X.2014.12.032
段汐,杨群,陈兵,李媛祯
DUAN Xi,YANG Qun,CHEN Bing and LI Yuan-zhen
摘要: 针对加入导向性局部搜索(Guided Local Search,GLS)的蚁群算法(Ant Colony Optimization,ACO)容易过早收敛的问题,提出一种带有摄动的导向性蚁群算法(Perturbation Guided Ant Colony Optimization,PGACO),该算法在当前解表现出过早收敛的趋势时,采用摄动(Perturbation)方式干扰解构建过程,使当前解移动到其邻域空间,从而产生一个新的可行解来避免算法过早收敛,提高算法求解的精度。实验结果表明,PGACO能有效地改善过早收敛问题,获得更优的可行解和执行速度,同时具有更强的全局搜索能力,能进一步提高算法的性能。
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