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Module Descriptor School of Computer Science and Statistics

Module CodeST2006
Module Short Title
Semester TaughtSemester 1 and 2
Contact Hours

2 hours lectures in both Semester 1 and 2 with weekly assignments in Semester 1 and 1 hour lab per week for Semester 2

Module PersonnelAssistant Professor Mary Sharp and Assistant Lecturer Brett Houlding 
Learning Outcomes

By the end of Semester 1 students should be able to:

  • Identify an infeasible problem, a problem with multiple solutions or the presence of degeneracy
  • Describe how to find an initial basic feasible solution to a linear program
  • Conduct a parametric analysis on a coefficient in the objective function
  • Define and formulate a balanced transportation problem and solve
  • Describe how to solve integer programs with a branch and bound algorithm
  • Formulate a 0–1 integer program, put into standard form and solve with a branch and bound algorithm  

By the end of Semester 2 students should be able to:  

  • the concepts and terminology involved in Simulation;
  • different kinds of simulation techniques;
  • how and when it is used and be familiar with a range of application examples;
  • how to apply a simulation using appropriate software;
  • its limitations      
Learning Aims

Semester 1 This course is based on developing and solving mathematical models of real life problems.  The students receive a theoretical introduction to the fundamental elements of a mathematical model. Modelling techniques are taught to solve problems in many domains.  

Semester 2: Introduction to Simulation. To introduce the concepts, ideas and techniques involved in Simulation.  

Module Content

Semester 1

  • Formulate and solve Linear and Goal Programming problems using the Simplex Method
  • Perform Sensitivity Analysis on the output from a Linear and Goal Programming problem
  • Formulate and solve Transportation, Transhipment and Assignment problems
  • Formulate a 0 – 1 Linear Programming problem and solve using the Cutting Plane and Branch and Bound Methods
  • Analyse networks for the Chinese Postman and Travelling Salesman Problems
  • Other relevant mathematical models  

Semester 2

Specific topics addressed in this module include:  

  • Entities, attributes and variables;
  • Events;
  • Resources;
  • Queues;
  • Steady-state models and transients;
  • Software for simulation;
  • Statistical analysis of output;  
Recommended Reading List

Semester 1

There is no set Bibliography for Semester 1. Advice as to course texts will be given in class.  

Semester 2

  1. J. Banks et al, Discrete-Event System Simulation, Pearson, 5th  edition (2010).  
  2. A. F.  Seila et al, Applied Simulation Modeling, Thompson, 2003.  
  3. A. M. Law, W.D. Kelton, Simulation Modeling, McGraw-Hill, 3th  edition  (2000).  
Module Prerequisites


Assessment Details

20% Course work and 80% Examination (3 hours) 

Module Website
Academic Year of Data2017/18