计算机工程与应用2019，Vol.55Issue(15)：47-58,12.DOI:10.3778/j.issn.1002-8331.1810-0334
求解约束优化问题的自适应人工蜂群算法
Self-Adaptive Artificial Bee Colony Algorithm for Constrained Optimization Problem
摘要
Abstract
A Self-Adaptive Artificial Bee Colony(SA-ABC)algorithm is proposed for constrained optimization problem. To make the initial colony scattered evenly on the search area, the opposite learning initialization is employed. For constraint handling, an adaptive selection strategy is designed, which can balance the feasible individuals and infeasible individuals. Furthermore, to improve the optimal ability of SA-ABC, the best-lead search equation is used in onlooker bee phase. To exam the efficiency, SA-ABC algorithm is tested on 13 well-known benchmark test functions, and the experi-mental results are compared with other state-of-art algorithms. The analyses of the experimental results suggest that the SA-ABC algorithm outperforms or performs similarly to other algorithms.关键词
自适应选择策略/人工蜂群算法/反学习初始化/约束优化Key words
adaptive selection strategy/ artificial bee colony algorithm/ opposite learning initialization/ constrained optimization分类
信息技术与安全科学引用本文复制引用
王贞,李旭飞..求解约束优化问题的自适应人工蜂群算法[J].计算机工程与应用,2019,55(15):47-58,12.基金项目
宁夏高等学校科学研究项目(No.NGY2017168). （No.NGY2017168）
