BMAN70142 : Simulation & Risk Analysis

Credit rating 15
Teaching period(s) Semester 2
Aims

Analysing systems dominated by randomness and/or interactions or feedback between their constituent elements particularly challenging. Problems of this type include operational risk analysis, revenue management and improving operational process flow in service or manufacturing. This unit will focus on application of approaches developed to model such systems, including the basics of queuing theory, Markov processes, risk management, and in particular computer-based simulation.

Objectives (Learning outcomes)

 

  • Familiarity with the concepts and types of tools and techniques commonly used in analysing the performance of and risk in complex operational systems.
  • Experience in considering different approaches and their assumptions, advantages and disadvantages.
  • Ability to formulate, use and understand models of problem situations including, where appropriate, state-of-the-art software tools.

 

Assessment methods

Coursework project (50%

2h closed-book exam (50%)

Information

Informal Contact Method

  • Office Hours
  • Online Learning Activities (blogs, discussions, self assessment questions)

Course unit overview

The module provides and overview of simulation techniques and their use in supporting risk analysis and / or flow management of systems that are sufficiently complex to limit the applicability of other modelling approaches. In particular, the module covers and contrasts a variety of simulation concepts and approaches including Monte Carlo Simulation, Discrete Event Simulation and System Dynamics. The module further introduces Markov Chain Analysis and basic Queuing Theoretical models, and discusses the use of these mathematical approaches as a means of complementing and / or informing simulation. There is a focus on practical modelling work and students are introduced to a range of suitable software packages.

Teaching staff No available data to display.
Timetable Assessment written exam - 2 hours
Lectures - 20 hours
Seminars - 10 hours
Teaching and learning methods No available data to display.