Evolutionary Multi-objective Optimization in Uncertain Environments

Name: Evolutionary Multi-objective Optimization in Uncertain Environments
Brand: Springer, Berlin
SKU: 9783540959755
Price: 584.36 RON
Availability: InStock

Issues and Algorithms

Autor: Chi-Keong Goh, Kay C. Tan

Limbă:

Legare: Copertă tare

Editura: Springer, Berlin

Disponibilitate: În depozitul extern în cantități mici

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584.36 lei

Evolutionary algorithms are sophisticated search methods that have been found to be very efficient a...

Informații despre carte

Autor

Chi-Keong Goh, Kay C. Tan

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2009

Pagini

271

EAN

9783540959755

ISBN

3540959750

Enbook ID

01571313

Editura

Springer, Berlin

Greutate

582

Dimensiuni

161 x 243 x 17

Descriere completă

Evolutionary algorithms are sophisticated search methods that have been found to be very efficient and effective in solving complex real-world multi-objective problems where conventional optimization tools fail to work well. Despite the tremendous amount of work done in the development of these algorithms in the past decade, many researchers assume that the optimization problems are deterministic and uncertainties are rarely examined. §§The primary motivation of this book is to provide a comprehensive introduction on the design and application of evolutionary algorithms for multi-objective optimization in the presence of uncertainties. In this book, we hope to expose the readers to a range of optimization issues and concepts, and to encourage a greater degree of appreciation of evolutionary computation techniques and the exploration of new ideas that can better handle uncertainties. "Evolutionary Multi-Objective Optimization in Uncertain Environments: Issues and Algorithms" is intended for a wide readership and will be a valuable reference for engineers, researchers, senior undergraduates and graduate students who are interested in the areas of evolutionary multi-objective optimization and uncertainties.

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Evolutionary Multi-objective Optimization in Uncertain Environments

Issues and Algorithms

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