Production Planning by Mixed Integer Programming Springer Series in Operations Research and Financial Engineering

This textbook provides a comprehensive modeling, reformulation and optimization approach for solving production planning and 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 solving real life or industrial production planning problems (involving complex production structures with multiple production stages) using MIP modeling and reformulation approach. It is based on the twenty years worth 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 an introduction to MIP modeling and to planning systems, as well as 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 more complicated problems.

Reading this book will allow the reader to improve formulations of non-standard MIP models much more effectively and produce state-of-the-art models and algorithms.