The Supply Chain in Manufacturing, Distribution, and Transportation: Modeling, Optimization, and Applications

Reporting on cutting-edge research in production, distribution, and transportation, The Supply Chain in Manufacturing, Distribution, and Transportation: Modeling, Optimization, and Applications provides the understanding needed to tackle key problems within the supply chain. Viewing the supply chain as an integrated process with regard to tactical and operational planning, it details models to help you address the wide range of organizational issues that can adversely affect your supply chain.

This compilation of scholarly research work from academia and industry considers high-level production schedules, product sourcing, network alignment, distribution center layouts, transportation operations with stochastic demand, inventory planning, and day-to-day operations planning. The book is divided into three sections:

• Industrial and Service Applications of the Supply Chain
• Analytic Probabilistic Models in Supply Chain Problems
• Optimization Models of Supply Chain Problems

Because tactical and operational models rely on quality forecasts of demand, the text examines stochastic customer demand, coordination of supply chain functions, and solution algorithms. It reviews real-world business applications and case studies that illustrate the modeling solutions discussed.

About the Editors

Kenneth D. Lawrence, Ph.D., is a professor of Management and Marketing Science and Decision Support Systems in the School of Management at the New Jersey Institute of Technology. His professional employment includes over 20 years of technical management experience with AT&T as Director, Decision Support Systems and Marketing Demand Analysis; Hoffmann-La Roche, Inc.; Prudential Insurance; and the U.S. Army in forecasting, marketing planning and research, statistical analysis, and operations research. He is a full member of the Graduate Doctoral Faculty of Management at Rutgers, the State University of New Jersey, in the Department of Management Science and Information Systems. Lawrence has served as the doctoral chairman and thesis advisor for four Rutgers doctoral students. He is a member of the graduate faculty at NJIT in management, transportation, statistics, and industrial engineering. He is also an active participant in professional associations, including the Decision Sciences Institute, Institute of Management Science, Institute of Industrial Engineers, American Statistical Association, and Institute of Forecasters. He has conducted significant funded research projects in health care and transportation.

Lawrence is the Associate Editor of the Journal of Statistical Computation and Simulation and the Review of Quantitative Finance and Accounting, and also serves on the editorial boards of Computers and Operations Research and the Journal of Operations Management. His research work has been cited hundreds of times in 74 different journals, including Computers and Operations Research, International Journal of Forecasting, Journal of Marketing, Sloan Management Review, Management Science, Sloan Management Review, Technometrics, Applied Statistics, Interfaces, International Journal of Physical Distribution and Logistics, and the Journal of the Academy of Marketing Science. He has 275 publications in the areas of multicriteria decision analysis, management science, statistics, and forecasting, and his articles have appeared in more than 25 journals, including European Journal of Operational Research, Computers and Operations Research, Operational Research Quarterly, and International Journal of Forecasting and Technometrics.

Lawrence is the 1989 recipient of the Institute of Industrial Engineers Award for significant accomplishments in the theory and applications of operations research. He was recognized in the February 1993 issue of the Journal of Marketing for his significant contribution in developing a method of guessing in the no data case, for diffusion of new products, and for forecasting the timing and the magnitude of the peak in the adaption rate. Lawrence is also a member of the following honorary societies: Alpha Iota Delta (Decision Sciences Institute) and Beta Gamma Sigma (Schools of Management). He is the recipient of the 2002 Bright Ideas Award in the New Jersey Policy Research Organization and the New Jersey Business and Industry Associates for his work in auditing, for his use of a goal programming model to improve the efficiency of audit sampling.

In February 2004, Dean Howard Tuckman of Rutgers University appointed Lawrence as an Academic Research Fellow to the Center for Supply Chain Management, because “his reputation and strong body of research is quite impressive.” The Center’s corporate sponsors include Bayer HealthCare, Hoffmann-LaRoche, IBM, Johnson & Johnson, Merck, Novartis, PeopleSoft, Pfizer, PSE&G, Schering-Plough, and UPS.

The recognition of Professor Lawrence’s research work is found in its broad citation, in various sources, in publishing in the finest research publication outlets, and in the recognition of his research abilities and skills by publications in companies and journal editors who continually seek him as a referee and editor. Lawrence’s own editorial works are characterized by a thorough blend of the refereed process and contributions by highly recognized scholars, including Nobel Prize winners and chaired professors from both domestic and international universities who are considered worldwide experts in their fields. A majority of these publications are in blind-refereed publications. The Institute of Industrial Engineers honored Lawrence for his “significant accomplishments in the field of operations research, both in application and theory.”

Many of Lawrence’s works have been cited multiple times. The citations for his works are found in 74 research outlets and include hundreds of citations. Some articles published decades ago are often cited.

Lawrence’s research has been listed as breakthrough research by the Journal of the American Marketing Association over a period of 35 years. His research in the Rutgers doctoral program has resulted in the awarding of multiple doctoral degrees under his direction. Furthermore, his research expertise and skills have led to his frequent participation on other doctoral dissertation committees.

Another measure of the quality of his research work is a record of multiple fundings of his research work. Furthermore, his work with various high-quality publishing firms in the development of educational material for textbooks also signifies the high quality of his work.

Ronald K. Klimberg, Ph.D., is a Professor in the Decision and System Sciences Department of the Haub School of Business at Saint Joseph’s University, Philadelphia, Pennsylvania. He received his B.S. in Information Systems from the University of Maryland, his M.S. in Operations Research from George Washington University, and his Ph.D. in Systems Analysis and Economics for Public Decision-Making from the Johns Hopkins University. Before joining the faculty of Saint Joseph’s University in 1997, he was a professor at Boston University (10 years), an operations research analyst for the Food and Drug Administration (FDA) (10 years), and a consultant (7 years). Klimberg was the 2007 recipient of the Tengelmann Award for his excellence in scholarship, teaching, and research.

Klimberg’s research has been directed toward the development and application of quantitative methods, for example, statistics, forecasting, data mining, and management science techniques, such that the results add value to the organization and are effectively communicated. He has published over 30 articles and made over 30 presentations at national and international conferences in the areas of management science, information systems, statistics, and operations management. His current major interests include multiple criteria decision making (MCDM), multiple objective linear programming (MOLP), data envelopment analysis (DEA), facility location, data visualization, data mining, risk analysis, workforce scheduling, and modeling in general. He is currently a member of INFORMS, DSI, and MCDM.

Virginia M. Miori, Ph.D., is currently an Assistant Professor in the Decision and System Sciences Department of the Erivan J. Haub School of Business at Saint Joseph’s University in Philadelphia, Pennsylvania. She currently has several research streams, the most prolific being in the areas of supply chain modeling, production scheduling optimization, and transportation optimization. She is also working in the areas of health-care supply chain modeling and optimization, EMBA team evaluations using the Analytic Hierarchy Process, and statistical examination of ethical behavior and expectations among high school and college students.

Miori has 12 years of teaching experience and has accumulated more than 15 years of experience in developing and implementing operations research models. These models are applied to problems in the chemical industry, manufacturing industries, logistics, transportation, and supply chain management. She has published a number of articles and presented at numerous conferences. The presentations have been offered in both refereed and invited capacities.

An award for outstanding dissertation was presented to Miori by Drexel University for her work in stochastic truckload transportation optimization. An outstanding research award was also presented by Saint Joseph’s University for adapting her transportation scheduling model for use in the dairy production scheduling arena. This work eventually led to the development of a commercial scheduling optimization software product.

As for her extensive educational background, in 2006 Miori earned a doctorate in Operations Research from the Bennett S. LeBow College of Business at Drexel University. She also holds a Master of Science degree in Transportation from the School of Engineering and Applied Sciences at the University of Pennsylvania and a Master of Science degree in Operations Research from Case Western Reserve University.

Her teaching activities at Saint Joseph’s University include both undergraduate and graduate courses in business statistics, quantitative methods, research skills, foundations and applications of Six Sigma for manufacturing, foundations and applications of Six Sigma for service industries, developing decision-making competencies, foundations for business intelligence, and applications of business intelligence.