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Advances of Evolutionary Computation: Methods and Operators de Erik Cuevas

Advances of Evolutionary Computation: Methods and Operators: Studies in Computational Intelligence, cartea 629

Autor Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro
en Limba Engleză Hardback – 8 feb 2016
The goal of this book is topresent advances that discuss alternative Evolutionary Computation (EC) developmentsand non-conventional operators which have proved to be effective in the solutionof several complex problems. The book has been structured so that each chaptercan be read independently from the others. The book contains nine chapters withthe following themes: 1) Introduction, 2) the Social Spider Optimization (SSO),3) the States of Matter Search (SMS), 4) the collective animal behavior (CAB)algorithm, 5) the Allostatic Optimization (AO) method, 6) the Locust Search(LS) algorithm, 7) the Adaptive Population with Reduced Evaluations (APRE)method, 8) the multimodal CAB, 9) the constrained SSO method.
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Specificații

ISBN-13: 9783319285023
ISBN-10: 3319285025
Pagini: 263
Ilustrații: XIV, 202 p. 48 illus., 5 illus. in color.
Dimensiuni: 155 x 235 x 14 mm
Greutate: 0.49 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

Introduction.- A Swarm Global Optimization Algorithm Inspired in the Behavior of the Social-spider.-A States ofMatter Algorithm for Global Optimization.- An Algorithm for Global Optimization Inspiredby Collective Animal Behavior.- A Bio-inspired Evolutionary Algorithm: AllostaticOptimization.- Optimization Based on the Behavior of Locust Swarms.
 
 

Textul de pe ultima copertă

The goal of this book is topresent advances that discuss alternative Evolutionary Computation (EC) developmentsand non-conventional operators which have proved to be effective in the solutionof several complex problems. The book has been structured so that each chaptercan be read independently from the others. The book contains nine chapters withthe following themes: 1) Introduction, 2) the Social Spider Optimization (SSO),3) the States of Matter Search (SMS), 4) the collective animal behavior (CAB)algorithm, 5) the Allostatic Optimization (AO) method, 6) the Locust Search(LS) algorithm, 7) the Adaptive Population with Reduced Evaluations (APRE)method, 8) the multimodal CAB, 9) the constrained SSO method.

Caracteristici

Discusses recent advances and alternative developments in Evolutionary Computation Highlights nonconventional operators which prove to be effective in adapting a determined EC method to a specific problem Consists of self-contained chapters that can be read independently from the others Includes supplementary material: sn.pub/extras