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Manycriteria Optimization And Decision Analysis Stateoftheart Present Challenges And Future Perspectives Natural Computing Series 1st Ed 2023 Dimo Brockhoff

  • SKU: BELL-51158638
Manycriteria Optimization And Decision Analysis Stateoftheart Present Challenges And Future Perspectives Natural Computing Series 1st Ed 2023 Dimo Brockhoff
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Manycriteria Optimization And Decision Analysis Stateoftheart Present Challenges And Future Perspectives Natural Computing Series 1st Ed 2023 Dimo Brockhoff instant download after payment.

Publisher: Springer
File Extension: PDF
File size: 16.23 MB
Pages: 373
Author: Dimo Brockhoff, Michael Emmerich, Boris Naujoks, Robin Purshouse, (eds.)
ISBN: 9783031252624, 3031252624
Language: English
Year: 2023
Edition: 1st ed. 2023

Product desciption

Manycriteria Optimization And Decision Analysis Stateoftheart Present Challenges And Future Perspectives Natural Computing Series 1st Ed 2023 Dimo Brockhoff by Dimo Brockhoff, Michael Emmerich, Boris Naujoks, Robin Purshouse, (eds.) 9783031252624, 3031252624 instant download after payment.

This book presents the state-of-the-art, current challenges, and future perspectives for the field of many-criteria optimization and decision analysis. The field recognizes that real-life problems often involve trying to balance a multiplicity of considerations simultaneously – such as performance, cost, risk, sustainability, and quality. The field develops theory, methods and tools that can support decision makers in finding appropriate solutions when faced with many (typically more than three) such criteria at the same time.

The book consists of two parts: key research topics, and emerging topics. Part I begins with a general introduction to many-criteria optimization, perspectives from research leaders in real-world problems, and a contemporary survey of the attributes of problems of this kind. This part continues with chapters on fundamental aspects of many-criteria optimization, namely on order relations, quality measures, benchmarking, visualization, and theoretical considerations. Part II offers more specialized chapters on correlated objectives, heterogeneous objectives, Bayesian optimization, and game theory.

Written by leading experts across the field of many-criteria optimization, this book will be an essential resource for researchers in the fields of evolutionary computing, operations research, multiobjective optimization, and decision science.

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