计算机工程与应用2009，Vol.45Issue(31)：211-214,217,5.DOI:10.3778/j.issn.1002-8331.2009.31.063
求解约束优化的一个自适应杂交差分演化算法
Self-adaptive hybrid differential evolution with simulated annealing algorithm for constrained optimization
摘要
Abstract
A self-adaptive hybrid differential evolution with simulated annealing algorithm using a constraint-handling approach based on feasibility rules,termed SahDESAfr.is proposed to solve real-parameter constrained optimization problems.In the SahDESAfr algorithm, the choice of learning strategy and several critical control parameters are not required to be pre-specified.During evolution, the suitable learning strategy and parameters setting are gradually self-adapted according to the learning experience.A simple constraint-handling approach based on feasibility rules is employed to deal with inequation constraints/The performance of the SahDESAfr algorithm is evaluated on a set of well-know constrained optimization problems commonly adopted in the specialized literature.The performance of the SahDESAfr is evaluated on the set of 13 benchmark functions.The proposed approach is compared with respect to two techniques that are representative of the state-of-the-art in the area.Comparative study exposes the SahDESAfr as a competitive algorithm for constrained optimization.关键词
差分演化算法/模拟退火算法/自适应技术/约束优415/约束处理技术Key words
differential evolution algorithm/simulated annealing algorithm/ self-adaptation/ constrained optimization/ constraint -handling approach分类
信息技术与安全科学引用本文复制引用
胡中波,王曙霞,熊盛武,苏清华..求解约束优化的一个自适应杂交差分演化算法[J].计算机工程与应用,2009,45(31):211-214,217,5.基金项目
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60572015.No.40701153) （the National Natural Science Foundation of China under Grant No.60572015.No.40701153）
国家重点基础研究发展规划(973)(the National Grand Fundamental Research 973 Program of China under Grant No.2004CCA02500) （973）
武汉市科技攻关项目(No.200770834318). （No.200770834318）
