- Postgraduate Institute Elective
Contents
The course will cover a mix of topics in Operations Research. A prior background in basic topics in OR at the undergraduate level (for example, an exposure to Linear Programming and Applied Probability) will be helpful but not essential. The course will be self contained and will cover the basic topics from a graduate level text as required. These topics include theory and applications of optimization and theory and application of stochastic models of analysis and decision making.
Game theory and application; Applied models in queuing; Applications of dynamic programming; Multi-objective decision making ; data envelopment analysis; Modern heuristics for global optimization; Applications of O.R. in logistics and supply chain management.
References
-
V. Chvatal (1983), Linear Programming, W.H. Freeman, New York.
-
C. F. Daganzo (1999), Logistics Systems analysis, 3rd edition. Springer, Berlin.
-
S. Nahmias (2001), Production and Operations Analysis, 4th edition, Irwin, Chicago.
-
C. R. Reeves (1993), Modern Heuristic techniques for Combinational Problems, Orient Longman, Hyderabad.
-
D. P. Bertsekas (2001), Dynamic Programming and Optimal Control, 2nd Edition, Athena Scientific, Belmont, MA.
-
J. Pitman (1996), Probability, Narosa Publishing House, New Delhi.