Simulation while not an easy exercise in any manner, is a very important method to test what-if scenarios in a world where uncertainly is the norm of the situation. In a world where services are gaining more and more prominence, simulation exercise becomes the only method to experience reality without actually doing it – production area has already benefited long from the method. Think about the popularity of reality shows on TV – how those have changed our take on entertainment. Similarly, simulation is the reality show of business process world without actually investing in them.
Some overall questions will span the general class theme. For any given challenge,
§ How to model the given system
§ What data and knowledge about the data exist and what are the constraints
§ How to analyze the output for model validation
§ How to suggest improvements from the model and its behavior
STUDENT LEARNING OUTCOMES
At the conclusion of the course the student should have:
§ Gain an understanding of integrating business management principles and practice the theory in an interdisciplinary environment
§ Develop skills that are necessary to solidify a business situation using what-if scenarios
§ Obtain the knowledge and skill to analyze a business process – not just at high-level
§ Work as a member of a team in completing everyday business tasks and making decisions relating to the overall operation of the business and growth of the business
§ Apply critical thinking and problem solving skills in a rapidly evolving environment
§ Develop the skills necessary to effectively participate in primary business function:
SESSION |
| READING |
MODULE A BASIC SIMULATION MODELING |
1 | Introduction/course outline
The Nature of Simulation
Systems, Models and Simulation
Simulation with ExtendSim |
|
2 | Simulation of a Single Server Queuing System
Simulation of an Inventory System
Simulation with ExtendSim |
|
3 | Parallel/ Distributed Simulation
Simulation with ExtendSim |
|
4 | Steps in a Simulation Study
Other types of Simulation
Simulation with ExtendSim |
|
5 | Case Studies |  |
MODULE B – MODELNG COMPLEX SYSTEMS
|  |  |
6 | List Processing in Simulation
Simulation with ExtendSim |
|
MODULE C – SIMULATION SOFTWARE
|  |  |
7 | Introduction, Classification
Simulation with ExtendSim |
|
8 | Desirable Software Features
Simulation with ExtendSim |
|
9 | Simulation Software Demonstration
Simulation with ExtendSim |
|
10 | Simulation Software Demonstration
Simulation with ExtendSim/Simul8/others | Chapter 3 |
MODULE D – PROBABILITY AND STATISTICS
|  |  |
11 | Random Variables
Simulation with ExtendSim |
|
12 | Simulation Output Data and Stochastic Process
Simulation with ExtendSim |
|
13 | Simulation Output Data and Stochastic Process
Simulation with ExtendSim | Chapter 4 |
14 | Case Studies |  |
|  |  |
15 | Presentation of Assignment |  |
16 | Presentation of Assignment |  |
MODULE F – INPUT PROBABILITY DISTRIBUTIONS
|  |  |
17 | Useful Distributions
Simulation with ExtendSim |
|
MODULE G – RANDOM NUMBER GENERATORS
|  |  |
18 | Introduction, Generators
Simulation with ExtendSim |
|
MODULE H – RANDOM VARIATES
|  |  |
19 | Continuous and Discrete Random Variates
Simulation with ExtendSim |
|
|  |  |
20 | Student presentations |  |