计算机科学与探索Issue(12)：1502-1510,9.DOI:10.3778/j.issn.1673-9418.1409031
多种群多策略的并行差分进化算法
Parallel Differential Evolution with Multi-Population and Multi-Strategy
摘要
Abstract
In order to improve the accuracy and efficiency of parallel differential evolution (DE), this paper proposes a parallel differential evolution with multi-population and multi-strategy, which provides a way to rebustly address various optimization problems. This algorithm divides an initial population into several sub-populations, and then they evolve with different DE strategies. The sub-populations evolve independently at first, and then communicate with each other at regular intervals. By using the proposed multi-population and multi-strategy, the parallel realization of the algorithm can save the computation time while searching with different optimization strategies. The experi- mental results show that the proposed algorithm is feasible and effective for solving different optimization problems.关键词
多种群/多策略/并行/差分进化Key words
multi-population/multi-strategy/parallel/differential evolution分类
信息技术与安全科学引用本文复制引用
陈颖,林盈,胡晓敏..多种群多策略的并行差分进化算法[J].计算机科学与探索,2014,(12):1502-1510,9.基金项目
The National Natural Science Foundation of China under Grant Nos.61202130,61332002,61309003(国家自然科学基金) （国家自然科学基金）
the Natural Science Foundation of Guangdong Province of China under Grant No. S2012040007948(广东省自然科学基金) （广东省自然科学基金）
the Fundamental Research Funds for the Central Universities of China under Grant No.12lgpy47(中央高校基本科研业务费专项资金) （中央高校基本科研业务费专项资金）
the Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant No.20120171120027(高等学校博士学科点专项科研基金) （高等学校博士学科点专项科研基金）
