Prerequisite: Exposure to relevant concepts at undergraduate level and instructor consent
Concepts in discrete event system simulation; approaches based on event scheduling, process interaction and activity scanning. Examples of systems such as job shop scheduling & extensions, queuing systems, inventory systems. Use of linked lists in implementing some common data structures encountered in simulation. Simulation in C. Concepts of object oriented simulation. Simulation packages.
Overview of basic concepts from probability and statistics concerning random variables, correlation, estimation, confidence intervals, hypothesis testing. Generation and testing of random numbers. Generation of random variates, random vectors, correlated random variates and stochastic processes. Input modeling; useful probability distributions; hypothesizing families of distributions, estimation of parameters, testing goodness of fit. Simulation Output data analysis for a single system; statistical analyses for transient systems and systems in statistical equilibrium. Comparing alternative system configurations; confidence intervals, ranking and selection. Variance reduction techniques. Experimental design, sensitivity analysis and optimization.
Simulation of manufacturing systems.
- A. M. Law and W. D. Kelton (2000), Simulation Modeling and Analysis, 3rd Ed., McGraw Hill International - Industrial Engg. Series.
- J. Banks, J. S. Carson, B. L. Nelson and D. M. Nicol (2001), Discrete Event System Simulation, 3rd Ed., Pearson Education International Series.
- W. D. Kelton, R. P. Sadowski and D. A. Sadowski (1998), Simulation with Arena, McGraw Hill International-Industrial Engg. Series.
- Y. Langsam, M. J. Augenstein and A. M. Tenenbaum (1998), Data Structures Using C and C++, 2nd Ed., Prentice Hall (India).
- K. S. Trivedi (2001), Probability and Statistics with Reliability, Queuing and Computer Science Applications, Eastern Economy Edition, Prentice-Hall (India).