基于混沌局部搜索算子的人工蜂群算法

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1、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artif

2、icialbeecolonyalgorithmbasedonchaoslocalsearchoperatorwangxiang1*,lizhi.yong2,xuguo.yi3,wangyan4(1.schoolofcivilengineering,zhengzhouinstituteofaeronauticalindustrymanagement,zhengzhouhenan450015,china;2.departmentofmathematicsandphysics,zhengz

3、houinstituteofaeronauticalindustrymanagement,zhengzhouhenan450015,china;3.schoolofaccounting,zhengzhouinstituteofaeronauticalindustrymanagement,zhengzhouhenan450015,china;4.departmentofcomputerscienceandapplication,zhengzhouinstituteofaeronauticali

4、ndustrymanagement,zhengzhouhenan450015,chinaabstract:inordertoimprovetheabilityofartificialbeecolonyalgotithmatexploitation,anovelchaos-artificialbeecolonyalgorithmisproposedforcontinuousfunctionoptimizationproblems.anewchaoticlocalsearchoperatorisembedd

5、edintheframeworkofthenewalgorithm.thenewoperator,whosesearchradiusshrinkswiththeevolutiongeneration,candothelocalsearcharoundthebestfoodsource.thesimulationresultsshowthat:comparedwiththoseofartificialbeecolonyalgorithm,thesolutionqualityandtheconvergenc

6、espeedofthenewalgorithmarebetterforrosenbrockandtheconvergencespeedofthenewalgorithmisbetterforgriewankandrastrigin.inordertoimprovetheabilityofartificialbeecolony(abc)algorithmatexploitation,anewchaosartificialbeecolony(ch.abc)algorithmwasproposedforcon

7、tinuousfunctionoptimizationproblems.anewchaoticlocalsearchoperatorwasembeddedintheframeworkofthenewalgorithm.thenewoperator,whosesearchradiusshrinkswiththeevolutiongeneration,candothelocalsearcharoundthebestfoodsource.thesimulationresultsshowthat:compare

8、dwiththoseofabcalgorithm,thesolutionqualityandtheconvergencespeedofthenewalgorithmarebetterforrosenbrockandtheconvergencespeedofthenewalgorithmisbetterforgriewankandrastrigin.keywords:optimization;chaos;artificialbeecolon