# Courses

## Simulation, Loughborough University - 10th - 14th July 2017

**Please note we are unable to offer en suite accommodation for this course. All rooms will have shared facilities**

**ABSTRACT**

Simulation is one of the most widely used operational research techniques. It involves the development of an imitation on a computer of the system under study, followed by experimentation to understand and investigate improvements to the system. This course provides an understanding of simulation, with a focus on the mathematical and statistical principles of stochastic simulation modelling. The main technique of interest is discrete-event simulation, although other simulation techniques will be introduced.

**PRE-REQUISITES**

An understanding
of the basic principles of statistics including confidence intervals and
hypothesis testing.

It would be useful to read some parts of the following books.

*Statistical
Aspects
*Krzanowski, W.J.
2010.

*An Introduction to Statistical Modelling*. Wiley, Chichester, UK.

Makridakis, S. Wheelwright, S.C. and Hyndman, R.J. 1998.

*Forecasting: Methods and Applications*. 3

^{rd}ed., New York, Wiley.

*Simulation
Concepts
*Pidd, M. (2005).

*Computer Simulation in Management Science, 5*

^{th}*ed*. Wiley, Chichester, UK.

Robinson, S. (2014).

*Simulation: The Practice of Model Development and Use*. 2

^{nd}ed., Palgrave, UK.

*Banks et al. (2001) Discrete Event System Simulation
by (3 ^{rd} edition), Prentice Hall. (Chapter 12)*

*Law (2006) Simulation Modeling and Analysis (4*

^{th}edition). (Chapters 10-12)
**AIMS
**The aim of the
course is to provide an understanding of the mathematical and statistical
principles of stochastic simulation modelling. The specific objectives are as
follows:

To understand the alternative simulation methods and the requirements for simulation studies

To develop skills in simulation modelling and simulation computer packages

To understand the nature of, and approaches to, input data modelling

To be able to analyse the output from a simulation model using appropriate methods

**LEARNING
OUTCOMES
**

*Subject Knowledge and Understanding*

On completion of the course students will be expected to:

- Understand the basic principles of simulation and performing simulation studies.
Understand the basic theory of simulation analysis including input data analysis, experimentation and output analysis.

Understand the key stages in developing and using simulation models

To be aware of the strengths and limitations of the approaches covered.

On completion of the course students will be expected to:

Intellectual Skills

- Be able to develop and use a simulation model for a given problem situation.
- Be able to evaluate the quality of a simulation analysis

*Practical Skills*On completion of the course students will be expected to:

- Be familiar with the use of a simulation software package (SIMUL8).
Be able to follow an appropriate life-cycle for the development and use of simulation models

Be familiar with the use of statistical analysis software (e.g. Excel, Minitab, SPSS).

**PRINCIPAL TOPICS OF STUDY**

*1.1 Introduction to simulation methods (Monte Carlo, discrete-event, system dynamics and agent based simulation) and simulation software*

1. Principles of Simulation

1. Principles of Simulation

1.2 Generating random variates

1.3 Computing aspects of simulation

1.4 Simulation studies and the simulation modelling life-cycle

1.5 Model validation

*2. Random Sampling*

2.1 Random number generation

2.2 Sampling from distributions

2.3 Variance reduction methods

*3.1 Analysis of a single scenario – obtaining accurate results*

3. Introduction to Output Analysis

3. Introduction to Output Analysis

3.2 Basics of comparing multiple scenarios

*4.1 Time series analysis*

4. Experimental Design and Analysis

4. Experimental Design and Analysis

4.2 Experimental design

4.3 Metamodelling

4.4 Simulation optimisation

4.5 Bootstrapping (for input data modelling as well)

COVERAGE OF
WEB-BASED MATERIAL AVAILABLE IN ADVANCE

Material
intended for preliminary reading discussing basics of the statistical aspects
of simulation.

**Start Date:**07/10/2017**End Date:**14/07/2017**Location:**Loughborough University**Address:**Leicestershire**Postcode:**LE11 3TU