The application-oriented approach of this book addresses the art and science of mathematical modeling for the collection of problems that fit the MIP framework and also discusses the algorithms and associated practices that enable those models to be solved most efficiently. Throughout the book, reasoning and interpretation are exercised more often than rigorous mathematical proofs of theorems, which may be located in referenced articles. The authors have been very thorough in searching out and synthesizing various modeling and solution approaches that have appeared in disparate publications over the past 40 years. This book is a well-organized and comprehensive reference that eases the learning hurdles in integer programming and provides suggestions/guidelines for practice on the job. This book is organized in three parts: modeling, review of linear programming (LP) and network flows, and solutions. The first part (Chapters 1-6) includes areas of successful MIP applications, systematic modeling procedures, typical types of models, transformation of non-MIP models, automatic preprocessing for getting better formulation, and modeling of combinatorial optimization problems. The second part (Chapters 7-10) presents algebraic and geometric basic concepts of LP theory and network flows needed for understanding integer programming. The final part (Chapters 11-17) addresses classical and modern solution approaches as well as the key components that build an integrated software system capable of solving large-scale integer programming and combinatorial optimization problems. Three commercial modeling languages for large-scale IP problems are introduced in appendices.

Der-San Chen, PhD, is Professor Emeritus in the Department of Industrial Engineering at The University of Alabama. He has over thirty years of academic and consulting experience on the applications of linear programming, integer programming, optimization, and decision support systems. Dr. Chen currently focuses his research on modeling optimization problems arising in production, transportation, distribution, supply chain management, and the application of optimization and statistical software for problem solving.

Robert G. Batson, PhD, PE, is Professor of Construction Engineering at The University of Alabama, where he is also Director of Industrial Engineering Programs. A Fellow of the American Society for Quality Control, Dr. Batson has written numerous journal articles in his areas of research interest, which include operations research, applied statistics, and supply chain management.

Yu Dang, PhD, is Qualitative Manufacturing Analyst at Quickparts.com, a manufacturing services company that provides customers with an online e-commerce system to procure custom manufactured parts. She received her PhD in operations management from The University of Alabama in 2004.