首页> 外文会议>第一届智能网络与智能系统国际会议(ICINIS 2008)(The First International Conference on Intelligent Networks and Intelligent Systems)论文集 >A Coarse-Grained Genetic Algorithm for the Optimal Design of the Flexible Multi-body Model Vehicle Suspensions Based on Skeletons Implementing
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A Coarse-Grained Genetic Algorithm for the Optimal Design of the Flexible Multi-body Model Vehicle Suspensions Based on Skeletons Implementing

机译:基于骨架实现的柔性多体模型车辆悬架优化设计的粗粒遗传算法

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A parallel genetic algorithm based coarse-grained module for the optimal design of the flexible multibody model vehicle suspensions is presented and the skeleton implementing is constituted in this paper.this paper tests the algorithm on the cluster system.The results show that the application of the algorithm presented in this paper outperforms equivalent sequential genetic algorithms for the optimization and also improves the efficiency of the computing time.We also compare the coarse-grained genetic algorithm with the master-slave genetic algorithm,and find the result of the genetic algorithm based coarse-grained is better than the result of the parallel genetic algorithm based master-slave module.
机译:提出了一种基于并行遗传算法的粗粒度模块进行柔性多体模型汽车悬架的优化设计,并构造了骨架的实现。本文提出的算法在性能上优于同等顺序遗传算法,并且提高了计算效率。我们还将粗粒度遗传算法与主从遗传算法进行了比较,找到了基于遗传算法的粗略遗传算法的结果。比基于并行遗传算法的主从模块的结果更好。

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