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Evolutionary Multi-objective Optimization in Uncertain Enviro... - 9783540959755

Description: Evolutionary Multi-objective Optimization in Uncertain Environments Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Issues and Algorithms Author(s): Chi-Keong Goh, Kay Chen Tan Format: Hardback Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Germany Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K ISBN-13: 9783540959755, 978-3540959755 Synopsis 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.

Price: 73.32 GBP

Location: Aldershot

End Time: 2024-11-12T09:29:29.000Z

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Evolutionary Multi-objective Optimization in Uncertain Enviro... - 9783540959755

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Book Title: Evolutionary Multi-objective Optimization in Uncertain Environ...

Number of Pages: 271 Pages

Language: English

Publication Name: Evolutionary Multi-Objective Optimization in Uncertain Environments: Issues and Algorithms

Publisher: Springer-Verlag Berlin AND Heidelberg Gmbh & Co. KG

Publication Year: 2009

Subject: Engineering & Technology, Computer Science

Item Height: 235 mm

Item Weight: 1270 g

Type: Textbook

Author: Kay Chen Tan, Chi-Keong Goh

Series: Studies in Computational Intelligence

Item Width: 155 mm

Format: Hardcover

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