计算机工程Issue(9)：258-262,280,6.DOI:10.3969/j.issn.1000-3428.2013.09.058
蚁群和微分进化相融合的自适应优化算法
Self-adaption Optimization Algorithm with Fusion of Ant Colony and Differential Evolution
摘要
Abstract
An self-adaption hybrid optimization algorithm with fusion of Ant Colony(AC) algorithm and Differential Evolution(DE) algorithm is proposed to solve the problem of complicated function global optimization. The new algorithm utilizes DE algorithm with the mutation and crossover operation to avoid AC algorithm premature convergence, and utilizes the pheromone positive feedback effect to speed up evolutionary algorithm search, and automatically adjusts searching range. Experimental results show that compared to the AC algorithm and DE algorithm, this new algorithm greatly improves the global optimization search efficiency.关键词
蚁群算法/微分进化算法/信息素/融合算法/全局优化Key words
Ant Colony(AC) algorithm/Differential Evolution(DE) algorithm/pheromone/fusion algorithm/global optimization分类
信息技术与安全科学引用本文复制引用
魏林,付华,尹玉萍..蚁群和微分进化相融合的自适应优化算法[J].计算机工程,2013,(9):258-262,280,6.基金项目
国家自然科学基金资助项目(51274118,70971059)；辽宁省科技攻关计划基金资助项目(2011229011) （51274118,70971059）
