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MBA - Semester II - Quantitative Analysis for Business Decisions
Posted Date: 14 Dec 2007 Resource Type: Articles/Knowledge Sharing Category: Syllabus
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Posted By: Sri Member Level: Gold
Rating:  Points: 1
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The objective of the course is to provide the basic tools of Operations Research in solving the management problems through modeling and using mathematical approach.
*The students have to be provided with Random Number Table to solve problem in the examination
1. Quantitative Analysis: Nature and Scope – Quantitative Analysis as A frame work for Managerial Decisions; Analysing and Defining the Problem, Developing A Model, Selecting the Inputs, Coming Up With A Solution, Quantifying the Model and the Solution, Putting the Model to Work, Relationship Between the Quantitative Specialist and the Manager, Introduction to Goal (Multi-objective) and dynamic programming(Emphasis on conceptual framework – no numerical problems), Typical Applications of Operations Research .
2. Decision Making: Using Probabilities Introduction to Decision Theory, Steps In the Decision Making, the Different environments In Which Decisions Are Made, Criteria For Decision Making Under Uncertainty, Decision Making Under conditions of Risk, Discrete Random Variables Using the Expected Value Criterion With Continuously Distributed Random Variables, Utility as A Decision Criterion, Decision Trees, Graphic Displays of the Decision Making Process, Decision Making With an Active Opponent.
3. Linear Programming: Introduction to Maximization and Using Graphic Methods, the Simplex Method; Justification, interpretation of Significance of All Elements In the Simplex Tableau, the Simplex Solution to A Minimizing Problem -Duality and Sensitivity Analysis: Definition of the Dual Problem, Primal, Dual Relationships, Economic Interpretation of Duality, Dual Simplex Method, Sensitivity Or Post-optimality Analysis.
4. Transportation Models: Definition and Application of the Transportation Model, Solution of the Transportation Problem, the Assignment Model, Traveling Salesman Problem.
5. Game Theory: Introduction – Two Person Zero-Sum Games, Pure Strategies, Games with Saddle Point, Mixed strategies, Rules of Dominance, Solution Methods of Games without Saddle point – Algebraic, matrix and arithmetic methods.
6. Queuing Theory: Basic Elements of the Queuing Model, of the Poisson and Exponential Distributions, Queuing With Combined Arrivals and Departures, Queues With Priorities For Service, Tandem Or Series Queues, Obstacles In Modeling Queuing Systems, Data Gathering and Testing, Queuing Decision Models
7. Simulation: Nature and Scope, Applications, Types of simulation, Discrete Simulation Approaches, Role of Random Numbers, Gathering Observations In Simulation, Inventory Example, Queuing Examples, Simulation Languages.
8. P.E.R.T. & C.P.M. and Replacement Model: Drawing networks – identifying critical path – probability of completing the project within given time- project crashing – optimum cost and optimum duration. Replacement models comprising single replacement and group replacement.
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