Co-evolutionary particle swarm optimization for min-max problems using Gaussian distribution

R. Krohling, F. Hoffmann, L. Coelho
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引用次数: 65

Abstract

Previous work presented an approach based on coevolutionary particle swarm optimization (Co-PSO) to solve constrained optimization problems formulated as min-max problems. Preliminary results demonstrated that Co-PSO constitutes a promising approach to solve constrained optimization problems. However the difficulty to obtain fine tuning of the solution using a uniform distribution became evident. In this paper, a modified PSO using a Gaussian distribution is applied in the context of Co-PSO. The modified Co-PSO is tested on some benchmark optimization problems and the results show a superior performance compared to the standard Co-PSO.
基于高斯分布的最小-最大问题的协同进化粒子群优化
先前的工作提出了一种基于协同进化粒子群优化(Co-PSO)的方法来解决表示为最小-最大问题的约束优化问题。初步结果表明,Co-PSO是一种很有前途的求解约束优化问题的方法。然而,使用均匀分布来获得解决方案的微调的困难变得明显。本文将一种基于高斯分布的改进粒子群算法应用于Co-PSO。在一些基准优化问题上对改进的Co-PSO进行了测试,结果表明与标准Co-PSO相比,改进的Co-PSO具有更好的性能。
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