Parameter Setting for Knowledge Evolution Algorithm

摘要：

Knowledge evolution algorithm (KEA) is a new optimization algorithm relies on the mechanism of knowledge evolution, and a series of parameters used in the algorithm play an important role in the optimization performance. Based on the knapsack problems, basic principles of parameter setting are proposed by using simulation experiments, which are beneficial to further application and promotion of the algorithm.

关键词： Knowledge Evolution Algorithm Parameter Setting Knapsack Problem Optimization

作者: XU Mengjun MA Huimin

作者单位: Business school, Univ. of Shanghai for S & T, Shanghai, 200093, China Business school, Shanghai Dianji University, Shanghai, 201306, China

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 2421-2426

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）