一种融合改进模拟退火技术的新型遗传算法  

New genetic algorithm syncretized the improved simulated annealing

作　　者：余冬梅[1] 张秋余[1] 伊华伟[1] 

机构地区：[1]兰州理工大学计算机与通信学院,甘肃兰州730050

出　　处：《计算机应用》2005年第10期2392-2394,共3页journal of Computer Applications

基　　金：国家科技攻关计划项目(2001BA201A32);国家863计划项目(2002AA415270)

摘　　要：通过对传统遗传算法和模拟退火算法各自优缺点的分析,提出了一种新型遗传算法。算法以最优保留策略的遗传算法作为主体流程,在主体流程过程中融入改进的模拟退火技术,即设置双阈值和保留中间最优解来减少计算量,加快算法的收敛速度,从而为求得全局最优解提供了保障。通过对F6函数仿真试验,新型遗传算法的收敛速度和跳出局部最优的能力有很大提高。Based on the analysis of the advantages and disadvantages of the Genetic Algorithm and Simulated Annealing Algorithm, a new Genetic Algorithm was proposed. The genetic algorithm with optimum reservation strategy was served as the main flow of the new algorithm which syncretized the mechanism of improved simulated annealing. In order to get the global optimum solution, the improved simulated annealing took the double threshold value and kept the middle optimum solution to reduce the computing capacity and enhanced the convergence speed. Through the simulation test of function, the result indicates that the new algorithm can improve the convergence speed and the ability of jumping out the local optimum solution greatly.

关 键 词：遗传算法 最优保留策略 模拟退火算法 新型遗传算法 F6函数 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] TP18[自动化与计算机技术—计算机科学与技术]