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Logic-Based Benders Decomposition: Theory and Applications
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Datenträgertyp (RDA)
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Online-Ressource
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1. Person/Familie
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Hooker, John
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Titel
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Logic-Based Benders Decomposition: Theory and Applications
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Verantw.-ang.
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by John Hooker
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Auflage
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1st ed. 2024.
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Verlagsort
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Cham
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Verlag
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Springer
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E-Jahr
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2024
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ISBN
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978-3-031-45039-6
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Umfangsang./phys. Beschr. d. Sekundärform
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Online Ressource
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URL
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https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=3732497&site=ehost-live 
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Inhaltliche Zsfg.
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Introduction -- Inference Duality -- The Basic Logic-based Benders Method -- Classical Benders Decomposition -- Combinatorial Benders Cuts -- Stochastic and Robust Optimization -- LBBD and Decision Diagrams -- LBBD and Heuristic Methods -- Task Assignment and Scheduling -- .Vehicle Routing -- Shop, Factory, and Employee Scheduling -- Other Scheduling and Logistics Problems; Health-related Applications -- Network Design -- Other Applications.
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2. Inhaltliche Zsfg.
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This book is the first comprehensive guide to logic-based Benders decomposition (LBBD), a general and versatile method for breaking large, complex optimization problems into components that are small enough for practical solution. The author introduces logic-based Benders decomposition for optimization, which substantially generalizes the classical Benders method. It can reduce solution times by orders of magnitude and allows decomposition to be applied to a much wider variety of optimization problems. On the theoretical side, this book provides a full account of inference duality concepts that underlie LBBD, as well as a description of how LBBD can be combined with stochastic and robust optimization, heuristic methods, and decision diagrams. It also clarifies the connection between LBBD and combinatorial Benders cuts for mixed integer programming. On the practical side, it explains how LBBD has been applied to a rapidly growing variety of problem domains. After describing basic theory, this book provides a comprehensive review of the rapidly growing literature that describes these applications, in each case explaining how LBBD is adapted to the problem at hand. In doing so this work provides a sourcebook of ideas for applying LBBD to new problems as they arise.
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Bestand
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1
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Bestellt: SV
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