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On the Performance of Differential Evolution Variants in Constrained Structural Optimization

机译：关于差分演化变体在约束结构优化中的性能

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摘要

Constrained optimization is a highly important field of engineering as most real-world optimization problems are associated with one or several constraints. Such problems are often challenging to solve due to their complexity and high nonlinearity. Differential evolution (DE) is arguably one of the most versatile and stable population-based search algorithms that exhibits robustness to multi-modal problems and has shown to be very efficient when solving constrained global optimization problems. In this paper we investigate the performance of several DE variants existing in the literature such as the traditional DE, the composite DE (CoDE), the adaptive DE with optional external archive (JADE) and the self-adaptive DE (jDE and SaDE), for handling constrained structural optimization problems. The performance of each DE variant is quantified by using three well-known benchmark structures in 2D and 3D. It is shown that JADE, which updates control parameters in an adaptive way, truly exhibits superior performance and outperforms the other DE variants in all the cases examined.
机译：受约束优化是一个非常重要的工程领域，因为大多数现实世界优化问题与一个或多个约束相关联。由于它们的复杂性和高度的非线性，这些问题通常挑战。差分演进（DE）可以说是最通用和稳定的基于人口的搜索算法之一，对多模态问题具有鲁棒性，并且在解决受约束的全局优化问题时已经表现出非常有效。在本文中，我们调查了文献中存在的几种变体的性能，例如传统的DE，复合DE（代码），Adaptive DE，具有可选的外部存档（玉）和自适应DE（JDE和SADE），用于处理受约束的结构优化问题。通过在2D和3D中使用三个公知的基准结构来量化每个DE变型的性能。结果表明，玉器以自适应方式更新控制参数，真正表现出卓越的性能，并且在所有情况下均有卓越的模式。

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