并行遗传算法在汽车悬架系统参数优化设计中的应用研究  

THE APPLICATION RESEARCH OF PARALLEL GENETIC ALGORITHM IN PARAMETRIC OPTIMIZATION DESIGN OF VEHICLE SUSPENSIONS

作　　者：刘光远[1] 高瑞贞[1] 张京军[1] 楼康华[1] 

机构地区：[1]河北工程学院信息与电气工程学院,河北邯郸056038

出　　处：《计算机应用与软件》2006年第7期18-20,共3页Computer Applications and Software

基　　金：国家自然科学基金(50145007);河北省自然科学基金(502383);河北省教育厅博士基金资助(B200213)项目资助

摘　　要：汽车悬架系统是一种典型的复杂多体动力学系统。目前国内外对其进行优化设计的方法从大的方面主要分为两种:确定性优化方法和随机性优化方法。遗传算法作为一种典型的随机性方法,在处理此类问题时显示出了良好的特性。但是随着问题规模的不断扩大,传统遗传算法的计算效率已无法满足要求。本文将并行遗传算法应用于汽车悬架系统参数优化设计,并在集群系统上对其进行了测试。计算效率得到了很大提高,取得了满意效果。Vehicle suspensions system is a typical complex multi-body dynamics system. There are two optimization design means of that in the world now. They are ascertain and random optimization methods. Genetic algorithm is a typical random method and displays well speciality in dealing with that problem. But with the increase enlarge of problems＇ dimensions, the calculate efficiency of traditional genetic algorithm don＇t satisfy the need. Parallel genetic algorithm is applied to the parametric optimization design of vehicle suspensions in this paper. This program is tested on the cluster system. The calculating efficiency is greatly increasing and satisfactory result has been gained by it.

关 键 词：汽车悬架系统 并行遗传算法 集群系统 

分 类 号：TP273.1[自动化与计算机技术—检测技术与自动化装置] O242.23[自动化与计算机技术—控制科学与工程]