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MATH6004 Stochastic OR Methods

Module Overview

The Stochastic OR Techniques part introduces the concepts and applications of the following four topics: queuing systems, inventory systems, reliability theory and decision theory. Models and examples are also given to demonstrate applications of the topics. Discrete event simulation is taught separately via lectures and computer workshops. One of the pre-requisites for MATH6013

Aims and Objectives

Module Aims

• Provide the students with a grounding in the stochastic elements of operations research. • Understand how to implement and analyse a discrete event simulation model

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

  • demonstrate knowledge and understanding of the concepts and applications of the following five topics: queuing systems, inventory systems, reliability theory, decision theory and simulation.
  • demonstrate skills in technical report writing.
  • demonstrate practical skills in decision analysis, modelling queueing and inventory systems and calculating the reliability of systems.
  • demonstrate skills in team working.
  • understand how to implement and analyse a discrete event simulation model using Simul8 software.
  • demonstrate gained skills in using computer software and programming.

Syllabus

Queuing Systems: Basic elements of a queue and applications of queuing systems. Inventory System: EOQ models, newsboy models, inventory model with stochastic demand. Reliability Theory: Reliability of a component, reliability of a system, maintenance models, reliability and economics. Decision Theory: Bayes’ rule, value of information, Decision trees, and utility. Simulation: The emphasis is on simulation computing skills, which are developed in computer labs based on the SIMUL8 package. Lectures cover: the concept of randomness; and sampling from probability distributions including discrete and continuous models.

Learning and Teaching

Teaching and learning methods

Twelve 2-hour OR techniques lectures Twelve 1-hour OR techniques tutorial sessions Three 2-hour simulation lectures Six 1-hour simulation computer sessions

TypeHours
Independent Study96
Teaching54
Total study time150

Resources & Reading list

Hillier, F. Introduction to Operations Research. 

Ross, SM. Applied Probability Models with Optimization Applications. 

Schaum. Outline of Operations Research. 

Nelson, BL. Stochastic Modeling: Analysis & Simulation. 

Winston, WL. Operations Research: Applications and Algorithms. 

Assessment

Assessment Strategy

The summative coursework assessment will be on Simulation (one individual assignment & one group assignment) The referral/repeat assessment includes both coursework and examination. If the coursework was previously passed, it is not retaken.

Summative

MethodPercentage contribution
Closed book Examination  (2 hours) 70%
Coursework 30%

Repeat

MethodPercentage contribution
Closed book Examination 70%
Coursework 30%

Referral

MethodPercentage contribution
Closed book Examination 70%
Coursework 30%

Repeat Information

Repeat type: Internal & External

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