The course will enable students to -
Course Outcomes (Cos):
Course |
Learning outcome (at course level) |
Learning and teaching strategies |
Assessment Strategies |
|
Paper Code |
Paper Title |
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FSG 423 |
Operation Research (Theory) |
The Students will - CO103. Analyze decision-making situations in business and tools of decision science. CO104. Solve problems of Linear Programming (LP) for optimum allocation of resources using different approaches. CO105. Evaluate the real business problems by applying the knowledge of game theory. CO106. Predict the problems of service industry and analyse the concepts related to queuing theory . CO107. Students will solve the transportation and assignment problems and interpret the cost-effective decision. CO108. Students will analyze the uncertainty and risk situation of business and propose their solution with the decision theory analysis. |
Approach in teaching: Interactive Lectures, Discussion, Tutorials, Reading assignments, Team teaching
Learning activities for the students: Field activities, Presentation, Giving tasks |
Class test, Semester end examinations, Quiz, Solving Numerical problems in tutorials, Assignments, Class Presentation |
Quantitative Techniques: An Introduction, Statistical and Operations Research techniques, Scope and application of Quantitative Techniques, Scientific approach in decision-making, Limitation of these techniques.
Linear Programming: Mathematical formulation of problem. Graphical and Simplex Solutions of LPP. Primal and its Dual.
Game Theory– Meaning, Two Person zero sum game , Mix strategies.
Queuing Theory – meaning , concepts and problems related with Queuing Theory.
Transportation: Solving the problem. Testing the optimality MODI method.Cases of unbalanced problems, Degeneracy, Maximization objective, Multiple solutions and Prohibited Routes
Assignment: Solving the problem. Cases of unbalanced problems, multiple optimum solutions, maximization objective and unacceptable assignments
Decision Theory: Maximin, Minimax, and Maximax expected pay off andregret, Expected value of Perfect Information, Decision Tree Analysis.