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Non-Convex Multi-Objective Optimization

Panos M Pardalos author Julius Zilinskas author Antanas Žilinskas author

Format:Paperback

Publisher:Springer International Publishing AG

Published:15th Jun '18

Currently unavailable, and unfortunately no date known when it will be back

Non-Convex Multi-Objective Optimization cover

Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions. Multi-objective optimization methods facilitate designers, engineers, and researchers to make decisions on appropriate trade-offs between various conflicting goals. A variety of deterministic and stochastic multi-objective optimization methods are developed in this book. Beginning with basic concepts and a review of non-convex single-objective optimization problems; this book moves on to cover multi-objective branch and bound algorithms, worst-case optimal algorithms (for Lipschitz functions and bi-objective problems), statistical models based algorithms, and probabilistic branch and bound approach. Detailed descriptions of new algorithms for non-convex multi-objective optimization, their theoretical substantiation, and examples for practical applications to the cell formation problem in manufacturing engineering, the process design in chemical engineering, and business process management are included to aide researchers and graduate students in mathematics, computer science, engineering, economics, and business management.  

“Readers will definitely enjoy this book, because all surveyed topics are rigorously exposed. Moreover, since the main prerequisites are provided, the book is essentially self-contained and easy to read. The authors have also included many illustrative pictures that ensure a good understanding of technical concepts and results. … this book is an excellent reference for researchers and graduate students in both pure and applied mathematics, as well as other disciplines.” (Nicolae Popovici, Mathematical Reviews, August, 2018)​

ISBN: 9783319869810

Dimensions: unknown

Weight: 454g

192 pages

Softcover reprint of the original 1st ed. 2017