计算机与数字工程Issue(7)：1175-1177,1211,4.DOI:10.3969/j.issn1672-9722.2015.07.003
一种保持种群多样性的改进混洗蛙跳算法
Improved Shuffled Flog Leaping Algorithm Based on Keeping the Diversity of Population
摘要
Abstract
Shuffled flog leaping algorithm for optimization in function easily falls into local optimal solution and the pre‐mature quickly converges of such shortcomings .An improved shuffled flog leaping algorithm is proposed based on cloud model theory .The idea is to initialize the population through reverse learning mechanism .Individual evolution mode is im‐proved by density diversity of the optimal values of all groups which are calculated through dynamic change the multiplicity ratio .The simulation results show that the proposed algorithm has fine capability of finding global optimum .关键词
混洗蛙跳算法/反向学习/多样性/优化Key words
shuffled flog leaping algorithm/opposition-based learning/diversity/optimization分类
信息技术与安全科学引用本文复制引用
张强,刘丽杰,郭昊..一种保持种群多样性的改进混洗蛙跳算法[J].计算机与数字工程,2015,(7):1175-1177,1211,4.基金项目
黑龙江省教育厅项目（项目12541086）资助。 （）
