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Production Planning by Mixed Integer Programming (Springer Series in Operations Research and Financial Engineering) Hardback - 2006
by Pochet, Yves; Wolsey, Laurence A
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- Hardback
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Details
- Title Production Planning by Mixed Integer Programming (Springer Series in Operations Research and Financial Engineering)
- Author Pochet, Yves; Wolsey, Laurence A
- Binding Hardback
- Edition 1st
- Condition Used - Very good
- Pages 500
- Volumes 1
- Language ENG
- Publisher Springer, New York, NY
- Publication date 2006-04-19
- Features Bibliography, Index
- Bookseller's Inventory # 241123077
- ISBN 9780387299594 / 0387299599
- Weight 1.97 lbs (0.89 kg)
- Dimensions 9.56 x 6.34 x 1.14 in (24.28 x 16.10 x 2.90 cm)
- Size 6x1x9
- Category Mathematics
- Library of Congress subjects Production planning - Mathematical models, Physical distribution of goods -
- Library of Congress Catalogue Number 2005935294
- Dewey Decimal Code 658.500
- Quantity available 1
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From the publisher
From the rear cover
This 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.
