Full Title  System Simulation Modelling and Analysis 

Short Title  System Simulation Modelling 









Description 

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 
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. Leadtime 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. Generalpurpose simulation packages. Object oriented simulation. Trends in simulation software. Focus on SIMUL8 and @Risk (Excel addon). 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 pseudorandom 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. AcceptanceRejection 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. Inputoutput 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. 
Learning Outcomes 

On completion of this module the learner will/should be able to 

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% 
Module Dependencies 

Pre Requisite Modules 
None 
Co Requisite Modules 
None 
Incompatible Modules 
None 
Coursework Assessment Breakdown  % 

Course Work / Continuous Assessment  20 % 
End of Semester / Year Formal Examination  80 % 
Coursework Assessment Breakdown 

Description  Outcome Assessed  % of Total  Assessment Week 

Project Design and analyse own simulation  1,2,3,4,5,6,7,8,9  20  Any 
End Exam Assessment Breakdown 

Description  Outcome Assessed  % of Total  Assessment Week 

Final Exam One written 2.5 hour paper and one 2.5 hour practical exam  1,2,3,4,5,6,7,8,9  80  End of Term 
Distance Learning Mode Workload 

Type  Location  Description  Hours  Frequency  Avg Weekly Workload 

Total Average Weekly Learner Workload 0.00 Hours 

Part Time Mode Workload 

Type  Location  Description  Hours  Frequency  Avg Weekly Workload 

Lecture  Distance Learning Suite  Lecture  3  Weekly  3.00 
Independent Learning  UNKNOWN  Independent Learning  4  Weekly  4.00 
Total Average Weekly Learner Workload 3.00 Hours 

Full Time Mode Workload 

Type  Location  Description  Hours  Frequency  Avg Weekly Workload 

Lecture  Not Specified  Lecture  3  Weekly  3.00 
Independent Learning  UNKNOWN  Independent Learning  4  Weekly  4.00 
Total Average Weekly Learner Workload 3.00 Hours 

Online Learning Mode Workload 

Type  Location  Description  Hours  Frequency  Avg Weekly Workload 

Total Average Weekly Learner Workload 0.00 Hours 

Resources 

Book 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. DiscreteEvent System Simulation, 5 th Edition Prentice Hall 2010 Law, A.M. & Kelton, W.D. Simulation Modelling & Analysis, 4 th Edition McGrawHill 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 
Other Resources 
None 
Url Resources 
Additional Info 