Lecture 1 : Decision Analysis : Introduction (Repplace with the new one)

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Lecture 2 : Payoff Matrix

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Lecture 3 : Decision Making Under Risk

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Lecture 4 : Value of Information

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Lecture 5 : Probability Concepts

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Lecture 6 : Bayes Theorem

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Lecture 7 : Decision Tree

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Lecture 8 : Decision Problem with Experimentation

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Lecture 9 : Decision Problem with Experimentation (Contd.)

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Lecture 10 : Decision Problem Example

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Lecture 11 : Introduction to Waiting Lines

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Lecture 12 : Poisson and Exponential Distribution

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Lecture 13 : Birth and Death Process

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Lecture 14 : M/M/1 Queing Model

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Lecture 15 : Queuing Example

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Lecture 16 : Queuing Examples (Contd.)

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Lecture 17 : M/D/1 and M/M/s Queuing Models

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Lecture 18 : M/M/s and M/M/infinity Models

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Lecture 19 : Finite Queue Space and Queuing Cost Models

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Lecture 20 : Queuing Cost, Priority and Networking Models

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Lecture 21 : Introduction to Simulation

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Lecture 22 : Discrete-Event and Monte-Carlo Simulation

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Lecture 23 : Pseudo random Numbers

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Lecture 24 : Simulation Examples

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Lecture 25 : Generation of Random Variates

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Lecture 26 : Simulation Examples (Contd.)

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Lecture 27 : Monte-Carlo Simulation and Output Analysis

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Lecture 28 : Variance Reduction and Simulation Software

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Lecture 29 : Continuous Simulation and System Dynamics

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Lecture 30 : System Dynamics Example

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Lecture 31 : Introduction to Graph Theory

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Lecture 32 : Introduction (Contd.)

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Lecture 33 : Operations on a Graph, Tree and Spanning Tree

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Lecture 34 : Minimal Spanning Tree

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Lecture 35 : Cutsets

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Lecture 36 : Fundamental Circuits and Network Simplex Method

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Lecture 37 : Maximal Flow Problems

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Lecture 38 : Maximal Flow Problems (Contd.)

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Lecture 39 : Shortest Path Problems

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Lecture 40 : Shortest Path Problems (Contd.)

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