OPTIMAL TOLERANCE ALLOTMENT USING A GENETIC ALGORITHM AND TRUNCATED MONTE-CARLO SIMULATION

被引：59

作者：

LEE, J

JOHNSON, GE

机构：

[1] Design Laboratory, University of Michigan, Ann Arbor

来源：

COMPUTER-AIDED DESIGN | 1993年 / 25卷 / 09期

关键词：

TOLERANCE ALLOTMENT; TOLERANCE OPTIMIZATION; STOCHASTIC OPTIMIZATION; MONTE-CARLO SIMULATION; GENETIC ALGORITHMS;

D O I：

10.1016/0010-4485(93)90075-Y

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

As is typical of stochastic-optimization problems, the multi-variate integration of the probability-density function is the most difficult task in the optimal allotment of tolerances. In this paper, a truncated Monte Carlo simulation and a genetic algorithm are used as analysis (i.e. multivariate-integration) and synthesis (i.e. optimization) tools, respectively. The new method has performed robustly in limited experiments, and was able to provide a significant reduction in optimal cost when compared with results published in a previous study.

引用

页码：601 / 611

页数：11

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