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Operations Research
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Course Outcome |
Learning and teaching strategies |
Assessment Strategies |
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CO1: Solve linear programming problems using appropriate techniques and optimization solvers, interpret the results obtained. CO2: Determine optimal strategy for Minimization of Cost / Maximization of Profits of shipping of products from source to Destination using various methods, Finding initial basic feasible and optimal solution of the Transportation problems CO3: Optimize the allocation of resources in the best possible way using various techniques and minimize the cost or time of completion of number of jobs by number of persons CO4: Model competitive real-world phenomena using concepts from game theory. Analyse pure and mixed strategy games CO5: Implement optimal decisions under the situation of risk and uncertainty CO6: Calculate the average cost of being in queuing system and the cost of service are minimized. |
Approach in teaching: Interactive lectures and Discussion and Power point presentation Learning activities for the students: Self learning assignments, effective discussion, simulation and presentation |
CA test, Semester end examination, Presentation, Quiz, and Interaction |
Operations Research- Meaning, Nature, Scope and Role of Operations Research, Scientific approach in decision-making, Techniques of OR, Limitations of OR
Linear Programming-Mathematical formulation of Linear Programming problems and their solution using Graphic approach. Simplex method
Linear Programming- Special Cases- Unbounded solution, Multiple Solutions, Non-Feasible solutions, Degenerate solutions, Primal and its dual. Introduction to Sensitivity Analysis
Transportation-General structure of transportation problem, methods of finding initial basic feasible solution (NWCM, LCM & VAM), test for optimality (MODI Method), Cases of unbalanced problems, Degeneracy, Multiple solutions and Prohibited Routes.
Assignment- Solving the problem. Cases of unbalanced problems, multiple optimum solutions, maximization objective and unacceptable assignments Sequencing Problems- General Assumptions, Basic Terminology, Processing n-jobs through two machines, Processing n-jobs through three machines, Processing n-jobs through m- machines
Decision Theory-Decision-Making under certainty, uncertainty and risk, Decision tree analysis
Queuing theory-introduction, elementary queuing system, single channel queuing model ( with Poisson arrivals and exponential service times.)
Theory of Games-Two persons Zero Sum games. Markov’s analysis- Introduction, application, state transition matrix, n steps transition probabilities, Markov Chain Algorithm.
*Case studies related to entire topics are to be taught.
Suggested Readings-
- Shrivastava Shenoy Sharma, Quantitative Techniques in Management, New Age Publications
- J. K. Sharma, Operations Research”, McMillan India
- N. D. Vohra ,Quantitative Techniques in Management”, Tata McGraw Hill Publications
- Anderson Williams ,Quantitative Methods for Business, 10th Edition Thopson
- Tulisian, Quantitative Techniques Theory and Problems, Pearson Education.
- S. D. Sharma, Operations Research, Kedar Nath and Ram Nath & Co. Ltd.
