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An introduction to engineering optimisation methods

机译:工程优化方法简介

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Some engineering problems are simple., like linear analysis; others are difficuit, like non-linear analysis; but there is a third group: those that are complex. Complex problems are those where there are many possible answers that have to be explored and assessed before a decision is made as to which is the best one. This article will discuss the principal concepts of design optimisation, then look at the various suitable techniques and make suggestions as to where they might be used by structural engineers. These methods include quasi-Newton, gradient, simulated annealing, Monte Carlo, genetic algorithms, particle swarms, neural networks, form-finding, and evolutionary topology optimisation. While the article will not be exhaustive (which would take several books), it will provide sufficient examples and typical formulas so that those interested can start to explore this fascinating subject.
机译:一些工程问题很简单,例如线性分析;其他的则很困难,例如非线性分析;但是还有第三类:复杂的。复杂的问题是那些必须做出许多可能的答案并要做出决定的最佳答案之前,必须进行探讨和评估的问题。本文将讨论设计优化的主要概念,然后研究各种合适的技术,并就结构工程师可能在何处使用它们提出建议。这些方法包括拟牛顿法,梯度法,模拟退火法,蒙特卡洛法,遗传算法,粒子群,神经网络,寻形法和进化拓扑优化。尽管本文并不详尽(需要花费几本书),但它将提供足够的示例和典型公式,以便有兴趣的人可以开始探索这个引人入胜的主题。

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