Intelligent Evolutionary Optimization

By:

Xu, Hua [author.]

Contributor(s):

Yuan, Yuan [co-author]

Material type:

TextLanguage: English Publication details: Amsterdam : Elsevier, 2024.Description: xxiv, 362p. : ill. ; 24 cmISBN:

9780443274008

Subject(s):

Other classification:

B28931 R4

Summary: Intelligent Evolutionary Optimization introduces biologically-inspired intelligent optimization algorithms to address complex optimization problems and provide practical solutions for tackling combinatorial optimization problems. The book explores efficient search and optimization methods in high-dimensional spaces, particularly for high-dimensional multi-objective optimization problems, offering practical guidance and effective solutions across various domains. Providing practical solutions, methods, and tools to tackle complex optimization problems and enhance modern optimization techniques, this book will be a valuable resource for professionals seeking to enhance their understanding and proficiency in intelligent evolutionary optimization.

Item type:

Textual

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Holdings
Cover image	Item type	Current library	Home library	Collection	Shelving location	Call number	Materials specified	Vol info	URL	Copy number	Status	Notes	Date due	Barcode	Item holds	Item hold queue priority	Course reserves
	Textual	Central Science Library	Central Science Library			B28931 R4 (Browse shelf(Opens below))					Available			SL1655968

Includes appendix and index

Intelligent Evolutionary Optimization introduces biologically-inspired intelligent optimization algorithms to address complex optimization problems and provide practical solutions for tackling combinatorial optimization problems. The book explores efficient search and optimization methods in high-dimensional spaces, particularly for high-dimensional multi-objective optimization problems, offering practical guidance and effective solutions across various domains. Providing practical solutions, methods, and tools to tackle complex optimization problems and enhance modern optimization techniques, this book will be a valuable resource for professionals seeking to enhance their understanding and proficiency in intelligent evolutionary optimization.

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