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QUasi-Affine TRansformation Evolutionary (QUATRE) algorithm: A cooperative swarm based algorithm for global optimization

机译:拟仿射变换进化算法(QUATRE):一种基于合作群的全局优化算法

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This paper presents a new novel evolutionary approach named Quasi-Affine TRansformation Evolutionary (QUATRE) algorithm, which is a swarm based algorithm and use quasi-affine transformation approach for evolution. The paper also discusses the relation between QUATRE algorithm and other kinds of swarm based algorithms including Particle Swarm Optimization (PSO) variants and Differential Evolution (DE) variants. Comparisons and contrasts are made among the proposed QUATRE algorithm, state-of-the-art PSO variants and DE variants under CEC2013 test suite on real-parameter optimization and CEC2008 test suite on large-scale optimization. Experiment results show that our algorithm outperforms the other algorithms not only on real-parameter optimization but also on large-scale optimization. Moreover, our algorithm has a much more cooperative property that to some extent it can reduce the time complexity (better performance can be achieved by reducing number of generations required for a target optimum by increasing particle population size with the total number of function evaluations unchanged). In general, the proposed algorithm has excellent performance not only on uni-modal functions, but also on multi-modal functions even on higher dimension optimization problems. (C) 2016 Elsevier B.V. All rights reserved.
机译:本文提出了一种新的新的进化方法,称为拟仿射变换进化算法(QUATRE),它是一种基于群体的算法,并使用拟仿射变换方法进行进化。本文还讨论了QUATRE算法与其他基于群体的算法(包括粒子群优化(PSO)变体和差分进化(DE)变体)之间的关系。在实际参数优化的CEC2013测试套件和大规模优化的CEC2008测试套件下,对提出的QUATRE算法,最新的PSO变体和DE变体进行了比较和对比。实验结果表明,该算法不仅在实参数优化方面而且在大规模优化方面均优于其他算法。此外,我们的算法具有更强的协作性,可以在某种程度上降低时间复杂度(可以通过增加粒子总数来减少目标最佳值所需的世代数,而在不增加功能评估总数的情况下实现更好的性能) 。通常,所提出的算法不仅在单模态函数上,而且在多模态函数上,甚至在高维优化问题上,都具有出色的性能。 (C)2016 Elsevier B.V.保留所有权利。

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