摘要
受细菌趋化行为的启发,将细菌趋化行为中的吸引与排斥转换操作引入到果蝇优化算法中,提出基于细菌趋化的果蝇优化算法。该算法通过判断群体适应度方差是否为零来决定执行排斥操作(逃离最差个体)还是吸引操作(向最优个体靠近),解决果蝇优化算法中只向最优个体靠近,而导致种群多样性丢失引起的早熟收敛问题。对几种经典测试函数的仿真结果表明,新算法具有更好的全局搜索能力,在收敛速度、收敛可靠性及收敛精度上比果蝇优化算法有较大的提高。
In this paper,attraction and exclusion operations of bacterial chemotaxis were introduced into original Fruit Fly Optimization Algorithm（FOA）,and FOA based on Bacterial Chemotaxis（BCFOA） was proposed.Exclusion（to escape the worst individual） or attraction（to be attracted by the best individual） was decided to perform by judging the fitness variance is zero or no,so that the problem of premature convergence caused by the loss of population diversity,which resulted from the fact that individuals only were attracted by the best one in FOA,was solved.The experimental results show that the new algorithm has the advantages of better global searching ability,and faster and more precise convergence.
出处
《计算机应用》
CSCD
北大核心
2013年第4期964-966,1038,共4页
journal of Computer Applications
基金
国家自然科学基金资助项目(61063028)
甘肃省科技支撑计划项目(1011NKCA058)
甘肃省教育厅科研基金资助项目(1202-04)
甘肃省自然科学基金资助项目(1208RJZA133)
关键词
细菌趋化
果蝇优化算法
吸引
排斥
适应度方差
bacterial chemotaxis
fruit fly optimization algorithm
attraction
exclusion
fitness variance
