| Description |
1 online resource (xix, 468 pages) : illustrations |
| Contents |
Front Matter -- Modeling. Introduction -- Modeling and Models -- Transformation Using 0₆1 Variables -- Better Formulation by Preprocessing -- Modeling Combinatorial Optimization Problems I -- Modeling Combinatorial Optimization Problems II -- Review of Linear Programming and Network Flows. Linear Programming--Fundamentals -- Linear Programming: Geometric Concepts -- Linear Programming: Solution Methods -- Network Optimization Problems and Solutions -- Solutions. Classical Solution Approaches -- Branch-and-Cut Approach -- Branch-and-Price Approach -- Solution via Heuristics Relaxations and Partitioning -- Solutions with Commercial Software -- References -- Appendix: Answers to Selected Exercises -- Index |
|
Introduction -- Modeling and models -- Transformation using 0-1 variables -- Better formulation by preprocessing -- Modeling combinatorial optimization problems I -- Modeling combinatorial optimization problems II -- Linear programming : fundamentals -- Linear programming : geometric concepts -- Linear programming : solution methods -- Network optimization problems and solutions -- Classical solution approaches -- Branch-and-cut approach -- Branch-and-price approach -- Solution via heuristics, relaxations, and partitioning -- Solutions with commercial software -- Appendix : Answers to selected exercises |
| Summary |
"In order to fully comprehend the algorithms associated with integer programming, it is important to understand not only how algorithms work, but also why they work. Applied Integer Programming features a unique emphasis on this point, focusing on problem modeling and solution using commercial software. Taking an application-oriented approach, this book addresses the art and science of mathematical modeling related to the mixed integer programming (MIP) framework and discusses the algorithms and associated practices that enable those models to be solved most efficiently. The book begins with coverage of successful applications, systematic modeling procedures, typical model types, transformation of non-MIP models, combinatorial optimization problem models, and automatic preprocessing to obtain a better formulation. Subsequent chapters present algebraic and geometric basic concepts of linear programming theory and network flows needed for understanding integer programming. Finally, the book concludes with classical and modern solution approaches as well as the key components for building an integrated software system capable of solving large-scale integer programming and combinatorial optimization problems. Throughout the book, the authors demonstrate essential concepts through numerous examples and figures. Each new concept or algorithm is accompanied by a numerical example, and, where applicable, graphics are used to draw together diverse problems or approaches into a unified whole. In addition, features of solution approaches found in today's commercial software are identified throughout the book. Thoroughly classroom-tested, Applied Integer Programming is an excellent book for integer programming courses at the upper-undergraduate and graduate levels. It also serves as a well-organized reference for professionals, software developers, and analysts who work in the fields of applied mathematics, computer science, operations research, management science, and engineering and use integer-programming techniques to model and solve real-world optimization problems."--Publisher's web site |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Print version record |
| Subject |
Integer programming.
|
|
MATHEMATICS -- Linear & Nonlinear Programming.
|
|
Integer programming
|
|
Ganzzahlige Optimierung
|
| Form |
Electronic book
|
| Author |
Batson, Robert G., 1950-
|
|
Dang, Yu., 1977-
|
| ISBN |
9781118166000 |
|
1118166000 |
|
9781118165997 |
|
1118165993 |
|
9780470828885 |
|
0470828889 |
|
