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Non-Convex Multi-Objective Optimization (Paperback, Softcover reprint of the original 1st ed. 2017) Loot Price: R2,789
Discovery Miles 27 890
Non-Convex Multi-Objective Optimization (Paperback, Softcover reprint of the original 1st ed. 2017): Panos M. Pardalos, Antanas...

Non-Convex Multi-Objective Optimization (Paperback, Softcover reprint of the original 1st ed. 2017)

Panos M. Pardalos, Antanas Zilinskas, Julius Zilinskas

Series: Springer Optimization and Its Applications, 123

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Loot Price R2,789 Discovery Miles 27 890 | Repayment Terms: R261 pm x 12*

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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.

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Series: Springer Optimization and Its Applications, 123
Release date: June 2018
First published: 2017
Authors: Panos M. Pardalos • Antanas Zilinskas • Julius Zilinskas
Dimensions: 235 x 155 x 11mm (L x W x T)
Format: Paperback
Pages: 192
Edition: Softcover reprint of the original 1st ed. 2017
ISBN-13: 978-3-319-86981-0
Categories: Books > Computing & IT > General theory of computing > Data structures
Books > Computing & IT > Computer programming > Algorithms & procedures
Books > Computing & IT > Applications of computing > General
Books > Science & Mathematics > Mathematics > Algebra > General
Books > Science & Mathematics > Mathematics > Applied mathematics > General
LSN: 3-319-86981-7
Barcode: 9783319869810

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