B.E Artificial Intelligence and Machine Learning Operations Research Syllabus - Mumbai University 2026
This is the Fourth Year AI-ML syllabus under REV-2019 'C' Scheme, in force from the academic year 2023-24. The University has not yet published an NEP 2020 syllabus for this year of the degree, and this is the scheme its examinations are set on.
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Syllabus for Operations Research
Module 1: Introduction to Operations Research: Introduction, , Structure of the Mathematical Model, Limitations of Operations Research
- Linear Programming: Introduction, Linear Programming Problem, Requirements of LPP, Mathematical Formulation of LPP, Graphical method, Simplex Method Penalty Cost Method or Big M-method, Two Phase Method, Revised simplex method, Duality, Primal – Dual construction, Symmetric and Asymmetric Dual, Weak Duality Theorem, Complimentary Slackness Theorem, Main Duality Theorem, Dual Simplex Method, Sensitivity Analysis Transportation Problem: Formulation, solution, unbalanced Transportation problem. Finding basic feasible solutions – Northwest corner rule, least cost method and Vogel’s approximation method. Optimality test: the stepping stone method and MODI method. Assignment Problem: Introduction, Mathematical Formulation of the Problem, Hungarian Method Algorithm, Processing of n Jobs Through Two Machines and m Machines, Graphical Method of Two Jobs m Machines Problem Routing Problem, Travelling Salesman Problem Integer Programming Problem: Introduction, Types of Integer Programming Problems, Gomory’s cutting plane Algorithm, Branch and Bound Technique. Introduction to Decomposition algorithms.
Module 2
- Queuing models: queuing systems and structures, single server and multi-server models, Poisson input, exponential service, constant rate service, finite and infinite population
Module 3: Simulation: Introduction, Methodology of Simulation, Basic Concepts,
- Simulation Procedure, Application of Simulation Monte-Carlo Method: Introduction, Monte-Carlo Simulation, Applications of Simulation, Advantages of Simulation, Limitations of Simulation
Module 4
- Dynamic programming. Characteristics of dynamic programming. Dynamic programming approach for Priority Management employment smoothening, capital budgeting, Stage Coach/Shortest Path, cargo loading and Reliability problems.
Module 5
- Game Theory. Competitive games, rectangular game, saddle point, minimax (maximin) method of optimal strategies, value of the game. Solution of games with saddle points, dominance principle. Rectangular games without saddle point – mixed strategy for 2 X 2 games.
Module 6
- Inventory Models: Classical EOQ Models, EOQ Model with Price Breaks, EOQ with Shortage, Probabilistic EOQ Model,
REFERENCES
- 1 Taha, H.A. "Operations Research - An Introduction", Prentice Hall, (7th Edition), 2002.
- 2 Ravindran, A, Phillips, D. T and Solberg, J. J. "Operations Research: Principles and Practice", John Willey and Sons, 2nd Edition, 2009.
- 3 Hiller, F. S. and Liebermann, G. J. "Introduction to Operations Research", Tata McGraw Hill, 2002.
- 4 Operations Research, S. D. Sharma, KedarNath Ram Nath-Meerut.
- 5 Operations Research, KantiSwarup, P. K. Gupta and Man Mohan, Sultan Chand & Sons.
Reproduced from the University of Mumbai syllabus for B.E. (Artificial Intelligence and Machine Learning) under REV-2019 'C' Scheme, in force from the academic year 2023-24. Wording is as printed in that syllabus. Module numbering is as printed there too.
The complete syllabus
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