基于混沌局部搜索算子的人工蜂群算法摘要:在求解函数优化问题时，为了提升人工蜂群算法局部搜索能力，提出了一种新颖的混沌蜂群算法。新算法设计了一种混沌局部搜索算子，并将其嵌入蜂群算法框架中；该算子不仅能够实现在最优食物源周围局部搜索，还能够随着进化代数增加使搜索范围不断缩小。仿真实验结果表明,与人工蜂群算法相比，新算法在rosenbrock函数上，求解精度和收敛速度明显占优；此外新算法在多模函数griewank和rastrigin上，收敛速度明显占优。关键词:优化；混沌；人工蜂群算法；局部搜索artificialbeecolonyalgorithmbasedonchaoslocalsearchoperatorwangxiang1*,lizhi.yong2,xuguo.yi3,wangyan4(1.schoolofcivilengineering,zhengzhouinstituteofaeronauticalindustrymanagement,zhengzhouhenan450015,china;2.departmentofmathematicsandphysics,zhengzhouinstituteofaeronauticalindustrymanagement,zhengzhouhenan450015,china;3.schoolofaccounting,zhengzhouinstituteofaeronauticalindustrymanagement,zhengzhouhenan450015,china;4.departmentofcomputerscienceandapplication,zhengzhouinstituteofaeronauticalindustrymanagement,zhengzhouhenan450015,chinaabstract:inordertoimprovetheabilityofartificialbeecolonyalgotithmatexploitation,anovelchaos-artificialbeecolonyalgorithmisproposedforcontinuousfunctionoptimizationproblems.anewchaoticlocalsearchoperatorisembeddedintheframeworkofthenewalgorithm.thenewoperator,whosesearchradiusshrinkswiththeevolutiongeneration,candothelocalsearcharoundthebestfoodsource.thesimulationresultsshowthat:comparedwiththoseofartificialbeecolonyalgorithm,thesolutionqualityandtheconvergencespeedofthenewalgorithmarebetterforrosenbrockandtheconvergencespeedofthenewalgorithmisbetterforgriewankandrastrigin.inordertoimprovetheabilityofartificialbeecolony(abc)algorithmatexploitation,anewchaosartificialbeecolony(ch.abc)algorithmwasproposedforcontinuousfunctionoptimizationproblems.anewchaoticlocalsearchoperatorwasembeddedintheframeworkofthenewalgorithm.thenewoperator,whosesearchradiusshrinkswiththeevolutiongeneration,candothelocalsearcharoundth---本文来源于网络，仅供参考，勿照抄，如有侵权请联系删除---ebestfoodsource.thesimulationresultsshowthat:comparedwiththoseofabcalgorithm,thesolutionqualityandtheconvergencespeedofthenewalgorithmarebetterforrosenbrockandtheconvergencespeedofthenewalgorithmisbetterforgriewankandrastrigin.keywords:optimization;chaos;artificialbeecolony(abc)algorithm;chaosartificialbeecolony(ch.abc)algorithm;localsearch0引言2005年提出的人工蜂群［1-4］(artificialbeecolony,abc)算法是一种新颖的群智能算法，它具有全局寻优能力强的特点，故被广泛应用于无约束优化问题［5-8］以及离散优化问题［9］。近来，文献［5-8］都指出，求解函数优化问题时，abc算法存在全局探索能力强、局部开采能力差的缺陷，尤其是针对rosenbrock函数求解能力较差。为了增强abc算法的局部搜索能力，本文利用混沌序列的随机性、遍历性和规律性，设计了一种混沌局部搜索算子，并将其嵌入蜂群算法框架中，从而提出了新颖的混沌蜂群（chaosartificialbeecolony，ch.abc）算法。针对5个标准benchmark函数的仿真实验结果表明，新算法增强了abc算法的局部搜索能力，进而在一定程度上提升了求解质量。1混沌蜂群算法本文设计了一种新颖的ch.abc算法，其基本思想是利用混沌序列的随机性、遍历性和规律性，设计了一种混沌搜索算子，实现了在当前最优解周围进行局部搜索的目的，进而增强了abc算法的开采能力。1.1混沌蜂群算法的步骤新设计的ch.abc算法具体的实现步骤如下。步骤1食物源初始化。随机生成初始食物源种群的相关信息。步骤2雇佣...