Particle Swarm Optimizaton: A Physics-Based Approach (Synthesis Lectures on Computational Electromagnetics)

Mikki, Said M.; Kishk, Ahmed A.

ISBN 10: 3031005767 ISBN 13: 9783031005763
Published by Springer, 2008
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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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Title: Particle Swarm Optimizaton: A Physics-Based ...
Publisher: Springer
Publication Date: 2008
Binding: Soft cover
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Taschenbuch. Condition: Neu. Particle Swarm Optimizaton | A Physics-Based Approach | Ahmed A. Kishk (u. a.) | Taschenbuch | ix | Englisch | 2008 | Springer International Publishing | EAN 9783031005763 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Seller Inventory # 121975063

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9783031005763

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Taschenbuch. Condition: Neu. Neuware -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 /IndexSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 104 pp. Englisch. Seller Inventory # 9783031005763

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 104 pp. Englisch. Seller Inventory # 9783031005763

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Mikki, Said M.; Kishk, Ahmed A.
Published by Springer, 2008
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