000 04574nam a22005895i 4500
001 978-0-387-33477-6
003 DE-He213
005 20161121231025.0
007 cr nn 008mamaa
008 100301s2006 xxu| s |||| 0|eng d
020 _a9780387334776
_9978-0-387-33477-6
024 7 _a10.1007/0-387-33477-7
_2doi
050 4 _aTS155-TS194
072 7 _aKJMV
_2bicssc
072 7 _aBUS087000
_2bisacsh
082 0 4 _a658.5
_223
100 1 _aPochet, Yves.
_eauthor.
245 1 0 _aProduction Planning by Mixed Integer Programming
_h[electronic resource] /
_cby Yves Pochet, Laurence A. Wolsey.
264 1 _aNew York, NY :
_bSpringer New York,
_c2006.
300 _aXXIV, 500 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Series in Operations Research and Financial Engineering,
_x1431-8598
505 0 _aProduction Planning and MIP -- The Modeling and Optimization Approach -- Production Planning Models and Systems -- Mixed Integer Programming Algorithms -- Classification and Reformulation -- Reformulations in Practice -- Basic Polyhedral Combinatorics for Production Planning and MIP -- Mixed Integer Programming Algorithms and Decomposition Approaches -- Single-Item Uncapacitated Lot-Sizing -- Basic MIP and Fixed Cost Flow Models -- Single-Item Lot-Sizing -- Lot-Sizing with Capacities -- Backlogging and Start-Ups -- Single-Item Variants -- Multi-Item Lot-Sizing -- Multi-Item Single-Level Problems -- Multi-Level Lot-Sizing Problems -- Problem Solving -- Test Problems.
520 _aThis textbook provides a comprehensive modeling, reformulation and optimization approach for solving production planning and related supply chain planning problems, covering topics from a basic introduction to planning systems, mixed integer programming (MIP) models and algorithms through the advanced description of mathematical results in polyhedral combinatorics required to solve these problems. This book addresses the solution of real life or industrial production planning problems (involving complex production structures with multiple production stages) using a MIP modeling and reformulation approach. It is based on close to twenty years of research in which the authors have played a significant role. One of the goals of this book is to allow non-expert readers, students in business, engineering, applied mathematics and computer science to solve such problems using standard modeling tools and MIP software. To achieve this the book provides a unique collection of reformulation results, integrating them into a comprehensive modeling and reformulation approach, as well as an easy to use problem-solving library. Moreover this approach is demonstrated through a series of real life case studies, exercises and detailed illustrations. Graduate students and researchers in operations research, management, science and applied mathematics wishing to gain a deeper understanding of the formulations and mathematics underlying this approach will find this book useful because of its detailed treatment of the polyhedral structure of the basic lot-sizing problems and simple mixed integer sets that arise in the decomposition of more complicated problems. This book will allow the reader to improve formulations of non-standard MIP models and produce state-of-the-art models and algorithms.
650 0 _aBusiness.
650 0 _aProduction management.
650 0 _aOperations research.
650 0 _aDecision making.
650 0 _aSoftware engineering.
650 0 _aMathematical models.
650 0 _aManagement science.
650 0 _aIndustrial engineering.
650 0 _aProduction engineering.
650 1 4 _aBusiness and Management.
650 2 4 _aOperations Management.
650 2 4 _aMathematical Modeling and Industrial Mathematics.
650 2 4 _aSoftware Engineering/Programming and Operating Systems.
650 2 4 _aOperations Research, Management Science.
650 2 4 _aIndustrial and Production Engineering.
650 2 4 _aOperation Research/Decision Theory.
700 1 _aWolsey, Laurence A.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780387299594
830 0 _aSpringer Series in Operations Research and Financial Engineering,
_x1431-8598
856 4 0 _uhttp://dx.doi.org/10.1007/0-387-33477-7
912 _aZDB-2-SMA
950 _aMathematics and Statistics (Springer-11649)
999 _c507462
_d507462