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020 _a9783031450396
_9978-3-031-45039-6
024 7 _a10.1007/978-3-031-45039-6
_2doi
050 4 _aQA402.5-402.6
072 7 _aPBU
_2bicssc
072 7 _aMAT042000
_2bisacsh
072 7 _aPBU
_2thema
100 1 _aHooker, John.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_967303
245 1 0 _aLogic-Based Benders Decomposition
_h[electronic resource] :
_bTheory and Applications /
_cby John Hooker.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2024.
300 _aIX, 142 p. 13 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Operations Research and Applications,
_x2770-6311
505 0 _aIntroduction -- 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.
520 _aThis 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.
650 0 _aMathematical optimization.
_965522
650 0 _aOperations research.
_957943
650 0 _aMathematics.
_965523
650 0 _aProduction management.
_967141
650 1 4 _aOptimization.
_965528
650 2 4 _aOperations Research and Decision Theory.
_967143
650 2 4 _aApplications of Mathematics.
_965529
650 2 4 _aOperations Management.
_967304
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031450389
776 0 8 _iPrinted edition:
_z9783031450402
776 0 8 _iPrinted edition:
_z9783031450419
830 0 _aSynthesis Lectures on Operations Research and Applications,
_x2770-6311
_965533
856 4 0 _uhttps://doi.org/10.1007/978-3-031-45039-6
912 _aZDB-2-SXSC
999 _c56575
_d56575