惯性权值控制策略:粒子漫游行为

A. Engelbrecht
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引用次数: 0

摘要

粒子群优化(PSO)算法的性能对主要控制参数非常敏感。由于这种敏感性,已经开发了各种方法来动态调整这些控制参数的值,试图消除事先控制参数调整的必要性。这些自适应方法中有很多是在搜索过程中调整惯性权值的不同方法。最近的研究表明,这些适应性方法并不是很有效。本文补充了前人对不同惯性权值控制策略的研究,重点研究了不同控制策略下粒子的漫游行为。结果表明,许多惯性权值控制策略表现出过度的漫游行为,导致了搜索努力的浪费。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Inertia weight control strategies: Particle roaming behavior
The performance of particle swarm optimization (PSO) algorithms have shown to be very sensitive to the main control parameters. Due to this sensitivity, various approaches have been developed to dynamically adjust the value of these control parameters in an attempt to remove the necessity of prior control parameter tuning. A large number of these adaptive approaches are different ways in which the inertia weight value can be adjusted during the search process. Recent studies have shown that these adaptive approaches are not very efficient. This paper supplements previous studies of the different inertia weight control strategies, focusing on the roaming behavior of particles under the different control strategies. It is shown that a number of these inertia weight control strategies exhibit excessive roaming behavior, resulting in wasted search effort.
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