摘要
针对解决标准磷虾群算法在求解高维复杂优化问题时无法跳出局部最优,求解精度低的缺点,提出了一种基于互利共生和优胜劣汰的改进磷虾群算法。该算法首先对磷虾群(KH)算法采用互利共生策略,增强粒子间的信息交流,有效提高了信息传递效率,提高了磷虾个体的生存能力;并借优胜劣汰的进化机制提升了种群个体的质量,以此跳出局部最优寻找最优解。最后通过10个标准测试函数的对比实验,表明了该算法在全局搜索能力和求解精度上与其他2种算法相比都有着显著优势。
Aimed at the shortcoming of easy plunging into local optimum of krill herd algorithm（KH）in solving high dimensional complex optimization problems,an improved krill herd algorithm based on mutualism and random disturbance is proposed.First,the algorithm puts the strategy of mutualism into the standard KH,which enhances the exchange of particles＇ information,improves the efficiency of information transfer effectively and increases krill individual＇s ability of survival.Second,in order to avoid the premature convergence,this algorithm adopts the evolution of the survival of fittest in the natural selection mechanism to improve the quality of the individuals.Finally,the experiments simulating 12 benchmark standard test functions show that the algorithm has good effect in optimization capability and accuracy of solution,and is surperior to or highly competitive with other two kinds of algorithm.
出处
《太原理工大学学报》
CAS
北大核心
2018年第1期127-132,共6页
Journal of Taiyuan University of Technology
基金
国家自然科学基金资助项目(61561001)
校级研究生创新项目资助(YCX1783)
北方民族大学重点科研项目(2015KJ10)
关键词
磷虾群算法
互利共生
优胜劣汰
krill herd algorithm
mutualism
survival of the fittest
