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Supply Chain Modeling and Algorithms
Fall 2005
This course focuses on the application of management science and optimization
techniques to model the newest emerging supply chain operational planning problems
(such as reverse logistics, integrated production, inventory and distribution problems,
multi-partner pricing analysis, supply chain distribution network design, location analysis
and multi-modal transportation planning and scheduling, etc.) to meet the changing needs
of new generations of our Ph.D. students. The course also focuses on the analysis of
developing new search algorithms and error bound to effectively solve such practical
business decision and optimization problems with many complex constraints. Academic
researchers and selected industry executives will be invited to the classroom to present
the pipeline research results and new challenges encountered in supply chain
management practices.
Text: A collection of academic journal papers from the literature
Topics:
1. Overview of supply chain planning issues and new challenges to management science
and optimization techniques
2. Literature review for available research results on supply chain strategic planning
3. The integrated production, inventory, and distribution problems
. Case study: The IPID problem at G-Chemical Corporation
. Modeling and algorithm analysis
. Extensions of the G-Chemical IPID model
4. Using CPLEX as a solver to the IPID problems
5. The reverse logistics problems: The bi-flow network (a new network flow problem)
6. The mathematical programming based heuristics for reverse logistics problems
7. Branch and bound based search algorithms for PDPs
8. Special case analysis and polynomial solutions
9. Theoretical error bound analysis
10. Empirical performance studies: design and analysis
11. Multi-partner pricing models
12. Supply chain distribution network design: models and algorithms
13. Design the large scale distribution network for Time Magazine supply chain
14. Multi-modal transportation problems and scheduling algorithms for internationaldomestic shipping networks
15. Case studies for emerging supply chain logistics optimization problems
Supply Chain Modeling and Algorithms
Rutgers Business School, Fall 2005
Suggested Readings(Part I*):
Ball, M. and M. Magazine. The Design and Analysis of Heuristics. Networks, Vol.11, pp
215-219, 1981.
Chandra, P., and M. L. Fisher. Coordination of production and distribution planning.
European Journal of Operational Research, Vol. 72, No. 3, pp 503-517. 1994.
Chen, Z. L. Integrated Production and Distribution Operations: Taxonomy, Models, and
Review. Supply Chain Analysis in the E-Business Era (Edited by D. Simchi-Levi, D.
Wu, and Z.-J. Shen), Kluwer Academic Publishers, 2004.
Chen, Z. L., L. Lei, and H. Zhong. On the container vessel scheduling problem with
reverse flows (Under the second review) Operations Research Letters, 2005.
Chien, T. W., A. Balakrishnan & R. T. Wong. An Integrated Inventory Allocation and
Vehicle Routing Problem. Transportation Science, Vol. 23, No. 2, May 1989.
Desrochers, M. and F. Soumis. A Generalized Permanent Labeling Algorithm for the
Shortest Path Problem with Time Windows. INFOR, Vol. 26, No. 3, pp.191-212, 1988.
Dowlatshahi, S. Developing a Theory of Reverse Logistics. Interfaces, Vol. 30, No. 3,
pp 143-155, 2000.
Dror, M and M. Ball. Inventory/Routing: Reduction from an Annual to a Short-Period
Problem. Naval Research Logistics, Vol. 34, pp. 891-905, 1987.
Fisher, M. The Lagrangian Relaxation Method for Solving Integer Programming
Problems.
Management Science, Vol. 27, No. 1, pp. 1-17, 1981.
Geismar, N., G. Larporti, L. Lei and C. Sriskandarajah. The Integrated Production and
Transportation Scheduling Problem with Expiring Product and Non-Instantaneous
Transportation Time. (Under the second review) Journal on Computing, 2005.
Guide, V. D. R., V. Jayaraman, R. Srivastava and W. C. Benton. Supply Chain
Management for Recoverable Manufacturing Systems. Interfaces, Vol. 30, No. 3, pp
125-142, 2000.
Jayaraman V. and A. Ross. A Simulated Annealing Methodology to Distribution
Network Design and Management. European Journal of Operational Research, Vol.
144, pp 629-645, 2003.
Jayaraman V., R. Ratterson, and E. Rolland. The design of reverse distribution networks:
Models and solution procedures. European Journal of Operational Research, Vol.
150, pp. 128-149, 2003.
Lei, L., A. Ruszczynski, S. Liu, and S. Park. Optimizing the demand-supply
planning for The General Chemical Group (Under second review) IIE
Transactions, 2005
Lei, L. H. Zhong, and W. Chaovalitwongse. On the bi-directional flow production and
distribution problems (Under the second review) Journal on Computing, 2005.
Lei, L. and Q. Wang. On the profitability of a three-partner channel. Journal of
Operational Research Society (To appear), 2005.
Lenstra, J. K. and A. Rinnooy Kan. Compexity of Vehicle Routing and Scheduling
Problems. Networks, Vol.11, pp 221-227, 1981.
Renaud, J & F. F. Boctor. A Sweep-based Algorithm for the Fleet Size and Mix Vehicle
Routing Problem. European Journal of Operational Research, Vol. 140, pp 618-628,
2002.
(* Part II readings will be assigned during the semester)