安徽大学学报（自然科学版）Issue(3)：16-23,8.DOI:10.3969/j.issn.1000-2162.2014.03.004
改进人工蜂群算法求解非线性方程组
Improved artificial bee colony algorithm for solving nonlinear equations
摘要
Abstract
The traditional artificial bee colony algorithm converged slowly in dealing with the unimodal problems and got into local optimum easily when dealing with the multimodal problems. So a modified artificial bee colony algorithm was proposed, which took examples from the differential evolution operators. This modified algorithm introduced individual current optimal value and random vector in the random search process on the neighborhood of nectar, which sped up the convergence rate of the unimodal problems and to some level, prevented multimodal problems from easily getting into local optimum. This improved the search ability of the algorithm. Finally, the improved algorithm was used to solve some basic functions and nonlinear equations to test the performance of it. Experimental results showed that the new algorithm not only avoided effectively being trapped in local minima but also outperformed others in terms of convergence rate and accuracy.关键词
群智能/非线性方程组/人工蜂群算法/差分进化/随机向量Key words
swarm intelligence/nonlinear equations/artificial bee colony algorithm/differential evolution/random vector分类
信息技术与安全科学引用本文复制引用
汪继文,杨丹,邱剑锋,王心灵..改进人工蜂群算法求解非线性方程组[J].安徽大学学报（自然科学版）,2014,(3):16-23,8.基金项目
安徽省教育厅自然科学基金资助项目(KJ2013A009, KJ2012B038) （KJ2013A009, KJ2012B038）
安徽省优秀青年人才基金资助项目(2011SQ RL018) （2011SQ RL018）
安徽大学青年科学研究基金资助项目( KJQN1015) （ KJQN1015）
安徽大学研究生学术创新基金资助项目(10117700175) （10117700175）
