首页> 外文会议>Adaptive and Natural Computing Algorithms pt.1; Lecture Notes in Computer Science; 4431 >Optimal Design Centring Through a Hybrid Approach Based on Evolutionary Algorithms and Monte Carlo Simulation
【24h】

Optimal Design Centring Through a Hybrid Approach Based on Evolutionary Algorithms and Monte Carlo Simulation

机译:基于进化算法和蒙特卡洛模拟的混合方法优化设计居中

获取原文
获取原文并翻译 | 示例

摘要

In many situations a robust design could be expensive and decision-makers need to evaluate a design that is not robust, that is, a design with a probability of satisfying the design specifications (or yield) less than 100 %. In this paper we propose a procedure for centring a design that maximises the yield, given predefined component tolerances. The hybrid approach is based on the use of Evolutionary Algorithms, Interval Arithmetic and procedures to estimate the yield percentage. The effectiveness of the method is tested on a literature case. We compare the special evolutionary strategy (1+1) with a genetic algorithm and deterministic, statistical and interval-based procedures for yield estimation.
机译:在许多情况下,健壮的设计可能会很昂贵,决策者需要评估不健壮的设计,即,满足设计规格(或成品率)的可能性小于100%的设计。在本文中,我们提出了一种在给定预定义的组件公差的情况下对设计进行居中的方法,该方法可以使产量最大化。混合方法基于进化算法,区间算术和过程的使用来估计产量百分比。在文献案例中测试了该方法的有效性。我们将特殊的进化策略(1 + 1)与遗传算法以及确定性,统计性和基于区间的过程进行产量估算进行比较。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号