基于logistic模型的自适应差分进化算法  

Adaptive differential evolution algorithm based on logistic model

作　　者：陈华[1,2] 范宜仁[1] 邓少贵[1] 

机构地区：[1]中国石油大学(华东)测井重点实验室,山东东营257061 [2]中国石油大学(华东)数学与计算科学学院,山东东营257061

出　　处：《控制与决策》2011年第7期1105-1108,1112,共5页Control and Decision

基　　金：国家油气科技专项项目(2008ZX05035-02);山东省自然科学基金项目(Y2007F25);中央高校基本科研业务费专项项目(09CX04001A)

摘　　要：提出一种基于logistic模型的自适应差分进化算法.该算法在运行过程中可自动调节缩放因子和交叉概率因子的大小,能在算法初期保持种群多样性,提高全局最优值的搜索能力,而在算法后期,随着局部最优值搜索能力的提高算法渐趋稳定.对几种典型Benchmarks函数进行了测试,实验结果表明所提出的算法收敛速度快、计算精度高.An adaptive differential evolution algorithm based on logistic model is presented.The algorithm can automatically adjust scaling factor and crossover factor during the running time,so it can keep the individuals diversity and improve searching ability of global optimum in the population at the initial generations.However,the algorithm is gradually stabilized with searching ability of local optimum improved at a later time.Several classic Benchmarks functions are tested and the results show that the proposed algorithms have fast convergence and higher calculation accuracy.

关 键 词：自适应差分进化 LOGISTIC模型 缩放因子 交叉概率因子 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]