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Particle swarm optimization : a phys...

Kishk, Ahmed A.

Particle swarm optimization : a physics-based approach

紀錄類型:	書目-語言資料,印刷品 : 單行本
副題名:	a physics-based approach
作者:	MikkiSaid M.,
其他作者:	KishkAhmed A.,
出版地:	[San Rafael, Calif.]
出版者:	Morgan & Claypool Publishers;
出版年:	c2008
面頁冊數:	ix, 93 p.ill. : 24 cm.;
集叢名:	Synthesis lectures on computational electromagnetics#20
標題:	Mathematical optimization -
附註:	Includes bibliographical references (p. 79-84) and index
摘要註:	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
ISBN:	978-1-59829-614-3

Particle swarm optimization : a physics-based approach
Mikki, Said M.

Particle swarm optimization : a physics-based approach / Said M. Mikki and Ahmed A. Kishk - [San Rafael, Calif.] : Morgan & Claypool Publishers, c2008. - ix, 93 p. ; ill. ; 24 cm.. - (Synthesis lectures on computational electromagnetics ; #20).
Includes bibliographical references (p. 79-84) and index.
ISBN 978-1-59829-614-3ISBN 978-1-59829-615-0ISBN 1-59829-614-0ISBN 1-59829-615-9
Mathematical optimization

Kishk, Ahmed A.

Particle swarm optimization : a physics-based approach
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