Adding a diversity mechanism to a simple evolution strategy to solve constrained optimization problems

E. Mezura-Montes, C. Coello
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引用次数: 40

Abstract

In this paper, we propose the use of a simple evolution strategy (SES) (i.e., a (1 + /spl lambda/)-ES with self-adaptation that uses three tournament rules based on feasibility) coupled with a diversity mechanism to solve constrained optimization problems. The proposed mechanism is based on multiobjective optimization concepts taken from an approach called the niched-Pareto genetic algorithm (NPGA). The main advantage of the proposed approach is that it does not require the definition of any extra parameters, other than those required by an evolution strategy. The performance of the proposed approach is shown to be highly competitive with respect to other constraint-handling techniques representative of the state-of-the-art in the area when using a set of well-known benchmarks.
在简单进化策略中加入多样性机制以解决约束优化问题
在本文中,我们提出使用一个简单的进化策略(SES)(即(1 + /spl lambda/)-ES,具有自适应,使用基于可行性的三个竞赛规则)结合多样性机制来解决约束优化问题。所提出的机制是基于多目标优化概念,取自一种称为小生境-帕累托遗传算法(NPGA)的方法。所提出的方法的主要优点是,除了进化策略所需的参数外,它不需要定义任何额外的参数。当使用一组众所周知的基准时,所提出的方法的性能显示出与代表该领域最先进的其他约束处理技术相比具有高度竞争力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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