# QLTY09031 2019 System Simulation Modelling and Analysis

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**Description**

Provides a comprehensive and practical treatment of all the important aspects of a simulation study, including modelling, simulation software, model verification and validation, input modelling, 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;*

**1.**

Describe the fundamentals of simulation and the techniques for developing simulation models.

**2.**

Use simulation as a decision support tool.

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Translate a business problem into a simulation model.

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Formulate an appropriate and correct discrete event simulation model of a system at an appropriate level of detail.

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Use an Excel spreadsheet with add-ins, e.g. @Risk, to build simulation models.

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Use SIMUL8 to model and solve a simulation problem.

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Identify the best probability distribution to describe the outcomes of a random variable.

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Generate random variates for discrete and continuous distributions.

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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. Two Assignments ( 1 x @Risk and 1 x SIMUL8) 20%.

**Final Examination **

1. One written 2.5 hour paper 40%

2. One computer based 2.5 hour exam involving @Risk & Simul8 40%

### Repeat Assessments

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### 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 & Continuous Assessment**

**End of Semester / Year Formal Exam**

### Coursework Assessment

Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
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1 | A SIMUL8 and an @Risk assignment | Continuous Assessment | Assignment | 20 % | Any | 1,2,3,4,5,6,7,8,9 |

### End of Semester / Year Assessment

Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
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1 | Final Exam - One written 2.5 hour Theory paper and one 2.5 hour practical simulation exam | Final Exam | Closed Book Exam | 80 % | End of Term | 1,2,3,4,5,6,7,8,9 |

### Full Time Mode Workload

Type | Location | Description | Hours | Frequency | Avg Workload |
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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 |
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Lecture | Distance Learning Suite | Lecture | 1 | Weekly | 1.00 |

Independent Learning | UNKNOWN | Independent Learning | 4 | Weekly | 4.00 |

### Required & Recommended Book List

**Required Reading**

2014-09-22

*Simulation*Red Globe Press

ISBN 1137328029 ISBN-13 9781137328021

The new edition of this successful textbook provides a comprehensive introduction to simulation, foregrounding the topic as an applied problem-solving tool. Guiding readers through the key stages in a simulation project in terms of both the technical requirements and the project management issues surrounding it, the book will enable students to develop appropriate valid conceptual models, perform simulation experiments, analyse the results and draw insightful conclusions. The authors engaging style and authoritative knowledge of the subject make the book as accessible as it is essential, drawing on case studies and complementary online content to encourage a critical engagement with the topic. This is an ideal textbook for those studying on upper level undergraduate and postgraduate degree courses in Business and Management and MBA programmes, and is a core text for those specialising in operations management. In addition, it is an important text for students taking Simulation modules on Engineering, Computer Science or Mathematics degree programmes.

**Required Reading**

2013-07-17

*Discrete-event System Simulation*

ISBN 1292024372 ISBN-13 9781292024370

For junior- and senior-level simulation courses in engineering, business, or computer science. While most books on simulation focus on particular software tools, Discrete Event System Simulation examines the principles of modeling and analysis that translate to all such tools. This language-independent text explains the basic aspects of the technology, including the proper collection and analysis of data, the use of analytic techniques, verification and validation of models, and designing simulation experiments. It offers an up-to-date treatment of simulation of manufacturing and material handling systems, computer systems, and computer networks. Students and instructors will find a variety of resources at the associated website, www.bcnn.net/, including simulation source code for download, additional exercises and solutions, web links and errata.

**Required Reading**

2014-01-22

*Simulation Modeling and Analysis*McGraw-Hill Education

ISBN 0073401323 ISBN-13 9780073401324

Since the publication of the first edition in 1982, the goal of Simulation Modeling and Analysis has always been to provide a comprehensive, state-of-the-art, and technically correct treatment of all important aspects of a simulation study. The book strives to make this material understandable by the use of intuition and numerous figures, examples, and problems. It is equally well suited for use in university courses, simulation practice, and self-study. The book is widely regarded as the bible of simulation and now has more than 155,000 copies in print and has been cited more than 14,000 times. The book can serve as the primary text for a variety of courses; for example: A first course in simulation at the junior, senior, or beginning-graduate-student level in Engineering, Manufacturing, Business, or Computer Science. At the end of such a course, the students will be prepared to carry out complete and correct simulation studies, and to take Advanced Simulation courses. A second course in simulation for graduate students in any of the above disciplines. After completing this course, the student should be familiar with the more advanced methodological issues involved in a simulation study, and should be prepared to understand and conduct simulation research. An introduction to simulation as part of a general course in Operations Research or Management Science.

**Recommended Reading**

2013

*Simulation*Academic Press

ISBN 9780124158252 ISBN-13 0124158250

"In formulating a stochastic model to describe a real phenomenon, it used to be that one compromised between choosing a model that is a realistic replica of the actual situation and choosing one whose mathematical analysis is tractable. That is, there did not seem to be any payoff in choosing a model that faithfully conformed to the phenomenon under study if it were not possible to mathematically analyze that model. Similar considerations have led to the concentration on asymptotic or steady-state results as opposed to the more useful ones on transient time. However, the relatively recent advent of fast and inexpensive computational power has opened up another approach--namely, to try to model the phenomenon as faithfully as possible and then to rely on a simulation study to analyze it"--

**Recommended Reading**

2018-01-01

*Practical Management Science*Cengage Learning

ISBN 9781337406659 ISBN-13 1337406651

Take full advantage of the power of spreadsheet modeling with the guidance in PRACTICAL MANAGEMENT SCIENCE, 6E, geared entirely to Excel 2016. This edition integrates modeling into all functional areas of business -- finance, marketing, operations management -- using real examples and real data. The book emphasizes applied, relevant learning while presenting the right amount of theory to ensure readers gain a strong foundation. Exercises offer practical, hands-on experience working with the methodologies. The authors focus on modeling rather than algebraic formulations or memorization of particular models. This edition provides new and updated cases as well as a new chapter on data mining. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

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