Evolutionary Constrained Optimization (Paperback, Softcover reprint of the original 1st ed. 2015)


This book makes available a self-contained collection of modern research addressing the general constrained optimization problems using evolutionary algorithms. Broadly the topics covered include constraint handling for single and multi-objective optimizations; penalty function based methodology; multi-objective based methodology; new constraint handling mechanism; hybrid methodology; scaling issues in constrained optimization; design of scalable test problems; parameter adaptation in constrained optimization; handling of integer, discrete and mix variables in addition to continuous variables; application of constraint handling techniques to real-world problems; and constrained optimization in dynamic environment. There is also a separate chapter on hybrid optimization, which is gaining lots of popularity nowadays due to its capability of bridging the gap between evolutionary and classical optimization. The material in the book is useful to researchers, novice, and experts alike. The book will also be useful for classroom teaching and future research.

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Product Description

This book makes available a self-contained collection of modern research addressing the general constrained optimization problems using evolutionary algorithms. Broadly the topics covered include constraint handling for single and multi-objective optimizations; penalty function based methodology; multi-objective based methodology; new constraint handling mechanism; hybrid methodology; scaling issues in constrained optimization; design of scalable test problems; parameter adaptation in constrained optimization; handling of integer, discrete and mix variables in addition to continuous variables; application of constraint handling techniques to real-world problems; and constrained optimization in dynamic environment. There is also a separate chapter on hybrid optimization, which is gaining lots of popularity nowadays due to its capability of bridging the gap between evolutionary and classical optimization. The material in the book is useful to researchers, novice, and experts alike. The book will also be useful for classroom teaching and future research.

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Product Details

General

Imprint

Springer, India, Private Ltd

Country of origin

India

Series

Infosys Science Foundation Series in Applied Sciences and Engineering

Release date

August 2016

Availability

Expected to ship within 10 - 15 working days

First published

2015

Editors

,

Dimensions

235 x 155 x 18mm (L x W x T)

Format

Paperback

Pages

319

Edition

Softcover reprint of the original 1st ed. 2015

ISBN-13

978-81-322-3505-7

Barcode

9788132235057

Categories

LSN

81-322-3505-3



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