IL4102 Operation Research Syllabus:
IL4102 Operation Research Syllabus – Anna University PG Syllabus Regulation 2021
COURSE OBJECTIVES
To provide students the knowledge of optimization techniques and approaches. Formulate a realworld problem as a mathematical model and finding solutions
To enable the students to learn about revised simplex method and sensitivity analysis of LPP.
To solve networking problems like transportation, Assignment, Maximal flow , Minimum spanning tree and shortest path problems
To learn about Decision making under uncertainty and certainty conditions,.
To learn various Queuing models
UNIT I LINEAR PROGRAMMING
Introduction to Operations Research – assumptions of Linear Programming Problems – Formulations of linear programming problem – Graphical method. Solutions to LPP using simplex algorithm – Two phase method – Big M method
UNIT II ADVANCES IN LINEAR PROGRAMMING
Revised simplex method – primal dual relationships – Dual simplex algorithm – Sensitivity analysis – changes in RHS value – changes in Coefficient of constraint – Adding new constraint – Adding new variable.
UNIT III NETWORK ANALYSIS
Transportation problems: Northwest corner rule, Least cost method , Vogel’s approximation method – stepping stone method – MODI method – Unbalanced transportation – Assignment problem – Hungarian algorithm – Travelling salesman problem – project management. Minimum spanning tree problem: prim’s algorithm, Kruskal’s algorithm – Shortest path problem: Dijkstra’s algorithms, Floyds algorithm – maximal flow problem: Maximal-flow minimum-cut theorem – Maximal flow algorithm
UNIT IV DECISION AND GAME THEORY
Decision making under certainty – Decision making under risk – Decision making under uncertainty – Decision tree analysis –Introduction to MCDM; AHP. Game Theory – Two person zero sum games, pure and mixed strategies – Theory of dominance – Graphical Solution – Solving by LP
UNIT V QUEUING THEORY
Queuing theory terminology – Single server, multi server- limited and unlimited queue capacity limited and unlimited population.- Dynamic Programming
TOTAL: 60 PERIODS
COURSE OUTCOMES
CO1: Learned how to translate a real-world problem, given in words, into a mathematical Formulation
CO2: Learn to apply simplex algorithm for LPP.
CO3: Be able to build and solve Transportation Models and Assignment Models, maximal flow problem, minimum spanning tree and shortest path problem.
CO4: The students will be able to handle issues in Decision making under various conditions.
CO5: The students acquire capability in applying and using of queuing models for day today problems.
REFERENCES:
1. Hamdy A Taha, “Operations Research – An Introduction”, Pearson, 2017.
2. Panneerselvam .R, “Operations Research”, PHI, 2009.
3. Philips, Ravindran and Solberg, “Operations Research principles and practices”, John Wiley, 2007.
4. Ronald L Rardin, “Optimisation in Operations Research”, Pearson, 2018.
5. Srinivasan.. G, “Operations Research Principles and Applications”, PHI, 2017.