Brain Storm Optimization Algorithms : Concepts, Principles and Applications

Cheng, Shi; Shi, Yuhui

ISBN 10: 3030150690 ISBN 13: 9783030150693

Editorial: Springer, 2019

Idioma: Ingl�s

Condici�n: Nuevo Encuadernaci�n de tapa dura

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Detalles bibliogr�ficos

T�tulo

Brain Storm Optimization Algorithms : Concepts, Principles and Applications

Editor

Springer

Fecha de publicaci�n

2019

Idioma

Ingl�s

ISBN 10

3030150690

ISBN 13

9783030150693

Encuadernaci�n

Encuadernaci�n de tapa dura

Estado

New

Cat�logos de vendedores

Acerca de

Sinopsis

Brain Storm Optimization (BSO) algorithms are a new kind of swarm intelligence method, which is based on the collective behavior of human beings, i.e., on the brainstorming process. Since the introduction of BSO algorithms in 2011, many studies on them have been conducted. They not only offer an optimization method, but could also be viewed as a framework of optimization techniques. The process employed in the algorithms could be simplified as a framework with two basic operations: the converging operation and the diverging operation. A "good enough" optimum could be obtained through recursive solution divergence and convergence. The resulting optimization algorithm would naturally have the capability of both convergence and divergence.

This book is primarily intended for researchers, engineers, and graduate students with an interest in BSO algorithms and their applications. The chapters cover various aspects of BSO algorithms, and collectively provide broad insights into what these algorithms have to offer. The book is ideally suited as a graduate-level textbook, whereby students may be tasked with the study of the rich variants of BSO algorithms that involves a hands-on implementation to demonstrate the utility and applicability of BSO algorithms in solving optimization problems.

De la contraportada

Brain Storm Optimization (BSO) algorithms are a new kind of swarm intelligence method, which is based on the collective behavior of human beings, i.e., on the brainstorming process. Since the introduction of BSO algorithms in 2011, many studies on them have been conducted. They not only offer an optimization method, but could also be viewed as a framework of optimization techniques. The process employed in the algorithms could be simplified as a framework with two basic operations: the converging operation and the diverging operation. A good enough optimum could be obtained through recursive solution divergence and convergence. The resulting optimization algorithm would naturally have the capability of both convergence and divergence.

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