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Optimization via Relaxation and Decomposition : Applications to Large-Scale Engineering Problems / by Gonzalo E. Constante-Flores, Antonio J. Conejo

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: International Series in Operations Research & Management Science ; 364Publisher: Cham : Springer Nature Switzerland, 2025Publisher: Cham : Imprint: Springer, 2025Description: 1 Online-Ressource (XVII, 262 p. 56 illus., 36 illus. in color.)ISBN:
  • 9783031874055
Subject(s): Additional physical formats: 9783031874048 | 9783031874062 | 9783031874079 | Erscheint auch als: 9783031874048 Druck-Ausgabe | Erscheint auch als: 9783031874062 Druck-Ausgabe | Erscheint auch als: 9783031874079 Druck-AusgabeDDC classification:
  • 658.403 23
DOI: DOI: 10.1007/978-3-031-87405-5Online resources: Summary: Relaxation and Decomposition -- Simplifying via Reformulation, Approximation, and Relaxation -- Approximating and Relaxing Optimization Problems -- Learning-Assisted Relaxations and Approximations -- Solving Optimization Problems with Complicating Variables -- Solving Optimization Problems via Lagrangian Decomposition -- Relaxations and Decomposition in Power Systems Operations.Summary: This book offers an up-to-date description of relaxation/approximation and decomposition techniques, demonstrating how their combined use efficiently solves large-scale optimization problems relevant to engineering, particularly in electrical, and industrial engineering, with a focus on energy. Specifically, it presents linear and nonlinear relaxations and approximations that are relevant to optimization problems, introduces complicating constraints and complicating variables decomposition techniques that can take advantage of relaxations and approximations, and examines their applications in the engineering field. Written in an accessible engineering language and filled with numerous illustrative examples and end-of-chapter exercises for all chapters, this book is a valuable resource for advanced undergraduate and graduate students, researchers, and practitioners in power engineering and industrial engineering. Moreover, business students with a keen interest in decision-making problems will also benefit greatly from its practical insights.PPN: PPN: 1926699777Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-BUM | ZDB-2-SXBM
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