QLTY09031 2013 System Simulation Modelling and Analysis
Provides a comprehensive and practical treatment of all the important aspects of a simulation study, including modeling, simulation software, model verification and validation, input modeling, random number generators, generating random variates, statistical design and the analysis of a simulation study
Learning Outcomes
On completion of this module the learner will/should be able to;
Describe the fundamentals of simulation and the techniques for developing simulation models.
Use simulation as a decision support tool.
Translate a business problem into a simulation model.
Formulate an appropriate and correct discrete event simulation model of a system at an appropriate level of detail.
Use an Excel spreadsheet with add-ins, e.g. @Risk, to build simulation models.
Use SIMUL8 to model and solve a simulation problem.
Identify the best probability distribution to describe the outcomes of a random variable.
Generate random variates for discrete and continuous distributions.
Analyse and interpret the results of a simulation model for making a business decision.
Teaching and Learning Strategies
Real world examples, case studies and published peer reviewed papers will be utilised, where possible.
Module Assessment Strategies
Continuous Assessment
1. Project work - Design and analyse ones own Simulation 20%.
Final Examination
1. One written 2.5 hour paper 40%
2. One computer based 2.5 hour exam involving @Risk & Simul8 40%
Indicative Syllabus
Basic simulation modelling
Introduction to Simulation. When is simulation appropriate. When is simulation not appropriate. Advantage and disadvantages of simulation. Areas of application. Components of a system. Discrete event and continuous simulation.
Simulation Examples
Illustration of general area of application. For example, simulation of a queueing system.
Spreadsheet Modelling
Developing a spreadsheet model. Concepts. Use of Solver. Optimisation modelling. Sensitivity analysis. Simulation of an Inventory system. Lead-time simulation. Supply chain and outsourcing simulation. Warranty model simulation.
Simulation Principles
Dynamic and stochastic systems. Concepts in discrete event simulation. Developing a discrete event model.
Simulation Software
Comparison of simulation packages with programming languages. Classification of simulation software. Desirable software features. General-purpose simulation packages. Object oriented simulation. Trends in simulation software. Focus on SIMUL8 and @Risk (Excel add-on).
Statistical Models in Simulation
Review of basic probability and statistical distributions. Discrete distributions. Continuous distributions. Empirical distributions. Models for arrival processes e.g. Poisson process.
Queueing Models
Characteristics of queueing systems. Queueing notation. Little's formula. Long run measures of performance of queueing systems. Server utilisation. Spreadsheet queueing simulation models.
Random Number Generators
Properties. Generation of pseudo-random numbers. Techniques for Generating random numbers. Linear congruential method. Combined linear congruential generators. Tests for random number.
Generating Random Variates
General programming methods for generating random variates. Inverse transform technique. Convolution method. Acceptance-Rejection method.
Input Modelling
Developing a useful model of input data. Collecting data, Identifying a probability distribution, parameter estimation, Goodness of fit testing. Selecting input models without data.
Model Verification and Validation
Verification of simulation models. Calibration and validation of models. Face validity. Validation of model assumptions. Input-output validation.
Output Analysis
Examination of data generated by simulation. Stochastic nature of output data. Output analysis for a single model. Measures of performance and their estimation. Comparing alternative system configurations.
Coursework & Assessment Breakdown
Coursework Assessment
Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
---|---|---|---|---|---|---|
1 | Project Design and analyse own simulation | Continuous Assessment | UNKNOWN | 20 % | Any | 1,2,3,4,5,6,7,8,9 |
End of Semester / Year Assessment
Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
---|---|---|---|---|---|---|
1 | Final Exam One written 2.5 hour paper and one 2.5 hour practical exam | Final Exam | UNKNOWN | 80 % | End of Term | 1,2,3,4,5,6,7,8,9 |
Full Time Mode Workload
Type | Location | Description | Hours | Frequency | Avg Workload |
---|---|---|---|---|---|
Lecture | Not Specified | Lecture | 3 | Weekly | 3.00 |
Independent Learning | UNKNOWN | Independent Learning | 4 | Weekly | 4.00 |
Part Time Mode Workload
Type | Location | Description | Hours | Frequency | Avg Workload |
---|---|---|---|---|---|
Lecture | Distance Learning Suite | Lecture | 3 | Weekly | 3.00 |
Independent Learning | UNKNOWN | Independent Learning | 4 | Weekly | 4.00 |
Module Resources
Authors |
Title |
Publishers |
Year |
Robinson, S., |
Simulation – The Practice of Model Development and Use |
John Wiley & Sons |
2004 |
Banks, J., Carson, J.S., Nelson, B. & Nicol, D. |
Discrete-Event System Simulation, 5^{th} Edition |
Prentice Hall |
2010 |
Law, A.M. & Kelton, W.D. |
Simulation Modelling & Analysis, 4^{th} Edition |
McGraw-Hill |
2006 |
Ross, S. |
Simulation, 5^{th} Edition, |
Academic Press |
2012 |
Winston, W. & Albright, S.C. |
Practical Management Science: Spreadsheet Modeling and Applications, 3^{rd} Edition |
South Western College Publishing |
2008 |
None
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