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Particle Swarm Optimizaton [electronic resource] : A Physics-Based Approach / by Said M. Mikki, Ahmed A. Kishk.

By: Mikki, Said M [author.].
Contributor(s): Kishk, Ahmed A [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Synthesis Lectures on Computational Electromagnetics: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2008Edition: 1st ed. 2008.Description: IX, 93 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031017049.Subject(s): Engineering | Electrical engineering | Telecommunication | Technology and Engineering | Electrical and Electronic Engineering | Microwaves, RF Engineering and Optical CommunicationsAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 620 Online resources: Click here to access online
Contents:
Introduction -- The Classical Particle Swarm Optimization Method -- Boundary Conditions for the PSO Method -- The Quantum Particle Swarm Optimization -- Bibliography.-Index.
In: Springer Nature eBookSummary: This 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 within the unified framework of the swarm dynamics. Table of Contents: Introduction / The Classical Particle Swarm Optimization Method / Boundary Conditions for the PSO Method / The Quantum Particle Swarm Optimization / Bibliography /Index.
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Introduction -- The Classical Particle Swarm Optimization Method -- Boundary Conditions for the PSO Method -- The Quantum Particle Swarm Optimization -- Bibliography.-Index.

This 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 within the unified framework of the swarm dynamics. Table of Contents: Introduction / The Classical Particle Swarm Optimization Method / Boundary Conditions for the PSO Method / The Quantum Particle Swarm Optimization / Bibliography /Index.

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