电子科技大学学报2017，Vol.46Issue(2)：419-425,7.DOI:10.3969/j.issn.1001-0548.2017.02.017
自适应混合文化蜂群算法求解连续空间优化问题
Adaptive Mixed Culture Artificial Bee Colony Algorithm for Continuous Space Optimization Problems
摘要
Abstract
An adaptive mixed culture artificial bee colony algorithm (AMC-ABC) is proposed to solve continuous space optimization problem. In the algorithm, community space is evolved by the improved group update way with optimal foraging theory; the knowledge of belief space is updated by the cloud model algorithm and optimal sorting differential mutation strategy; the outer space is evolved by chaos algorithm and opposition-based learning algorithm; and the knowledge exchange of three kinds of spatial is realized by adaptive acceptance operation and effect of operation. Simulation results of the typical complex functions show that the algorithm has fine the convergence precision and computing speed, particularly suitable for optimization the multimodal function.关键词
蜂群算法/文化算法/云模型/连续空间优化Key words
artificial bee colony algorithm (ABC)/cultural algorithm/cloud model/continuous space optimization分类
信息技术与安全科学引用本文复制引用
张强,李盼池,王梅..自适应混合文化蜂群算法求解连续空间优化问题[J].电子科技大学学报,2017,46(2):419-425,7.基金项目
国家自然科学基金(61170132) （61170132）
黑龙江省自然科学基金(F2015020) （F2015020）
黑龙江省教育厅项目(12541086) （12541086）
