计算机科学 ›› 2015, Vol. 42 ›› Issue (9): 240-245.doi: 10.11896/j.issn.1002-137X.2015.09.046
王奇琪,孙根云,王振杰,张爱竹,陈晓琳,黄丙湖
WANG Qi-qi, SUN Gen-yun, WANG Zhen-jie, ZHANG Ai-zhu, CHEN Xiao-lin and HUANG Bing-hu
摘要： 针对引力搜索算法(Gravitational Search Algorithm,GSA)收敛速度较快、易陷入局部最优的缺点,提出一种加入斥力的引力搜索算法RFGSA(Repulsion Force based Gravitational Search Algorithm)。该算法在引力搜索算法中引入斥力,即将一部分引力变为斥力,从而增加种群的多样性,有利于寻找全局最优。对10个基准测试函数进行优化的结果表明:该算法的收敛结果明显优于遗传算法、粒子群算法及原始的引力搜索算法。
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