Modeling operations research and business analytics - Fox, William P.; Burks, Robert E. (Boca Raton : CRC Press, 2025)
"This book provides sample exercises, techniques, and solutions to employ mathematical modeling to solve problems in Operations Research and Business Analytics. Each chapter begins with a scenario and includes exercises built on realistic problems faced by managers and others working in operations research, business analytics, and other fields employing applied mathematics. A set of assumptions is presented and then a model is formulated. A solution is offered followed by examples of how that model can be used to address related issues. Key elements of this book include the most common problems the authors have encountered over research and consulting including inventory theory, facilities location, linear and integer programming, assignment, transportation and shipping, critical path, dynamic programming, queuing models, simulation models, reliability of system, multi-attribute decision making and game theory. In the hands of an experienced professional, mathematical modeling can be a powerful tool. This book presents situations and models to help both professionals and students learn to employ these techniques to improve outcomes and to make addressing real business problems easier. The book is essential for all managers and others who would use mathematics to improve their problem-solving techniques. No previous exposure to mathematical modeling is required. The book can then be used for a first course on modeling, or for those with more experience who want to refresh their memories when they find themselves facing real-world problems. The problems chosen are presented to represent those faced by practitioners. The authors have been teaching mathematical modeling to students and professionals for nearly forty years. This book is presented to offer their experience and techniques to instructors, students, and professionals"--
Includes bibliographical references and index.
Keywords: Operations research; Business; Industrial management; Data processing