This course will equip students with essential Operations Research principles, techniques, and analytical skills to tackle real-world problems effectively, fostering critical thinking and decision-making abilities in diverse scenarios.
Course |
Learning outcome (at course level) |
Learning and teaching strategies |
Assessment Strategies |
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Course Code |
Course title |
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24MBAS 227 |
OPERATIONS RESEARCH (Theory) |
CO92: analyze real-world problems and determine whether they are suitable for Operations Research (OR) techniques CO93: evaluate the sensitivity of linear programming solutions to changes in input parameters, applying sensitivity analysis techniques to optimize decision-making processes. CO94: analyze transportation and assignment problems, identifying unbalanced scenarios, degeneracy, and multiple optimal solutions CO95: design and implement decision-making frameworks that integrate decision theory principles and queuing theory concepts CO96: evaluate the strategic implications of different game- theoretic strategies and assess the stability and equilibrium of Markov chains. CO97: Contribute effectively in course-specific interaction |
Approach in teaching: Interactive Lectures, Group Discussion, Tutorials, Case Study
Learning activities for the students: Self-learning assignments, presentations |
.Class test, Semester end examinations, Quiz, Assignments, Presentation |
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.
· 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.
· Softwares & Tools: Excel Solver and R Studio
· https://www.tes.com/resources/search/?authorId=21446845
· Operations Research, https://pubsonline.informs.org/journal/opre
· Management Science, https://pubsonline.informs.org/journal/mnsc