Springer Optimization and Its Applications- Non-Convex Multi-Objective Optimization
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Auteur:
Panos M. Pardalos
Antanas Zilinskas
Co-auteur:
Julius Zilinskas
- 9783319869810
- 15 juni 2018
- 192 pagina's
Samenvatting
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.
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.
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.
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- Oorspronkelijke releasedatum
- 15 juni 2018
- Aantal pagina's
- 192
Betrokkenen
- Hoofdauteur
- Panos M. Pardalos
- Tweede Auteur
- Antanas Zilinskas
- Co Auteur
- Julius Zilinskas
- Hoofduitgeverij
- Springer International Publishing Ag
Overige kenmerken
- Editie
- Softcover reprint of the original 1st ed. 2017
- Product breedte
- 155 mm
- Product lengte
- 235 mm
- Verpakking breedte
- 155 mm
- Verpakking hoogte
- 235 mm
- Verpakking lengte
- 235 mm
- Verpakkingsgewicht
- 454 g
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- EAN
- 9783319869810
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