基于遗传算法的机器可靠性优化

Ngnassi Djami Aslain Brisco, Nzié Wolfgang, D. Serge
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引用次数: 0

摘要

为了定义系统(机器)的可靠性网络,我们从一组以适当拓扑(串联、并联或并联-串联)排列的组件开始,选择性能/成本比率的最佳条款,并通过链接收集,目的是将它们组合起来。考虑到大量可能的组合,这个过程需要很长的时间和精力,这对分析人员来说变得乏味。因此,在设计任何产品时,使用适当的优化方法是必不可少的。然而,在尝试优化之前,有必要有一个可靠性评估方法。本文的目的是展示一种基于遗传算法的元启发式方法来提高机器的可靠性。为了实现这一目标,开发了一种由呈现遗传算法功能组成的方法。研究结果为最优解提出了一个可靠性网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Reliability Optimization by Genetic Algorithm Approach
To define the reliability network of a system (machine), we start with a set of components arranged in an appropriate topology (series, parallel, or parallel-series), choose the best terms of the ratio performance / cost, and gather by links with the aim to combine them. This process requires a long time and effort, given the very large number of possible combinations, which becomes tedious for the analyst. For this reason, it is essential to use an appropriate optimization approach when designing any product. However, before trying to optimize, it is necessary to have a reliability assessment method. The objective of this paper is to display a meta-heuristic method, which is sustained on the genetic algorithm (GA) to improve the machines reliability. To achieve this objective, a methodology that consists of presenting the functionalities of genetic algorithms is developed. The result achieved is the proposal of a reliability network for the optimal solution.
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