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Particle Swarm Optimization for Single Objective Continuous Space Problems: A Review

机译:单目标连续空间问题的粒子群算法研究进展

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摘要

This paper reviews recent studies on the Particle Swarm Optimization (PSO) algorithm. The review has been focused on high impact recent articles that have analyzed and/or modified PSO algorithms. This paper also presents some potential areas for future study.
机译:本文回顾了有关粒子群优化(PSO)算法的最新研究。这篇综述的重点是最近分析和/或修改过的PSO算法的高影响力文章。本文还提出了一些可能需要进一步研究的领域。

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  • 来源
    《Evolutionary computation》 |2017年第1期|1-54|共54页
  • 作者单位

    Department of Computer Science, The University of Adelaide, Adelaide, SA 5005, Australia. Also with the Centre for Advanced Imaging (CAI), the University of Queensland, Brisbane, QLD 4067, Australia, and Complexica Pty Ltd, Adelaide, SA 5021, Australia. mrbonyadi@cs.adelaide.edu.au, rezabny@gmail.com;

    Department of Computer Science, The University of Adelaide, Adelaide, SA 5005, Australia. Also with Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland, Polish-Japanese Institute of Information Technology, Warsaw, Poland, and Complexica Pty Ltd, Adelaide, SA 5021, Australia. zbyszek@cs.adelaide.edu.au;

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