Particle Swarm Optimization: A Physics-Based Approach

S. Mikki, A. Kishk
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引用次数: 52

Abstract

AbstractThis work aims to provide new introduction to the particle swarm optimization methods using a formal analogy with physical systems. By postulating that the swarm motion behaves similar to both classical and quantum particles, we establish a direct connection between what are usually assumed to be separate fields of study, optimization and physics. Within this framework, it becomes quite natural to derive the recently introduced quantum PSO algorithm from the Hamiltonian or the Lagrangian of the dynamical system. The physical theory of the PSO is used to suggest some improvements in the algorithm itself, like temperature acceleration techniques and the periodic boundary condition. At the end, we provide a panorama of applications demonstrating the power of the PSO, classical and quantum, in handling difficult engineering problems. The goal of this work is to provide a general multi-disciplinary view on various topics in physics, mathematics, and engineering by illustrating their interdependence wit...
粒子群优化:基于物理的方法
摘要本文通过对物理系统的形式化类比,对粒子群优化方法进行了新的介绍。通过假设群体运动的行为与经典粒子和量子粒子相似,我们在通常被认为是独立的研究领域、优化和物理学之间建立了直接联系。在这个框架下,从动力系统的哈密顿量或拉格朗日量推导出最近引入的量子粒子群算法就变得很自然了。利用粒子群的物理理论对算法本身进行了改进,如温度加速技术和周期边界条件。最后,我们提供了一个全景的应用,展示了PSO的力量,经典和量子,在处理困难的工程问题。这项工作的目标是通过说明物理学、数学和工程学的相互依存关系,为物理学、数学和工程学的各种主题提供一个一般的多学科观点。
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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