Supply Chain in Manufacturing, Distribution, and Transportation

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advanced supply chain planning case studies
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analysis
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B01=Kenneth D. Lawrence
B01=Ronald K. Klimberg
B01=Virginia M. Miori
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Customer Driven Supply Chain
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HCSC
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Integrated Supplier Selection
inventory optimization
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Manufacturing
Marginal Return
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network design algorithms
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Operational Supply Chain Planning
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probabilistic forecasting methods
Production Schedule
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stochastic demand modeling
Super Matrix
supplier collaboration strategies
Supply Chain
supply chain analytics
Supply Chain Management
Tactical Supply Chain Planning
Tardy Orders
Total Supply Chain Inventory
Transportation

Product details

  • ISBN 9781138372696
  • Weight: 610g
  • Dimensions: 156 x 234mm
  • Publication Date: 12 Jun 2019
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
  • Language: English
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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.

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 Mar