Games and Networks - BUSN6000

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Module delivery information

This module is not currently running in 2021 to 2022.

Overview

The module is divided into three main topics, namely Combinatorial Optimisation, Dynamic Programming and Game Theory. A more detailed listing of content is given below.

Combinatorial Optimisation:
The Shortest Path Problem
The Minimal Spanning Tree Problem
Flows in Networks
Scheduling Theory
Computational Complexity


Theory of Games:
Matrix Games – Pure Strategies
Matrix Games – Mixed Strategies
Bimatrix Games
N-person Games
Multi-criteria Decision Theory

Details

Contact hours

22 lectures, 10 seminars.

Lectures: 22
Seminars: 10
Independent study: 118
Total hours: 150

Method of assessment

80% 2-hour examination; 20% Coursework (four equally weighted components)

Indicative reading

Indicative Reading List:

W. L. Winston (2003). Operations Research: Applications and Algorithms. Andover: Cengage. Classmark T 57.6 (Recommended Text; we shall follow it closely)
H. Taha (2011). Operations Research: An Introduction. New York: Prentice Hall. Classmark HD29
E. L. Lawler (1976) Combinatorial Optimization: Networks and Matroids. New York: Holt, Rinehart & Winston. Classmark QA402.5

See the library reading list for this module (Canterbury)

Learning outcomes

Intended subject specific learning outcomes:

Understanding the underlying concepts and theory of Combinatorial Optimisation and Game Theory.
Representing a management problem in a mathematical or structured form, i.e. developing a model.
Analyse such models and hence solve problems.
Understanding the proofs of certain theorems in Game Theory and Combinatorial Optimisation.
Present their findings in a rigorous yet clear fashion.
Creating models of abstract problems in general terms, with an emphasis on mathematical rigour.

Intended generic learning outcomes:

Demonstrate a reasonable understanding of Mathematics.
Demonstrate skill in calculation and manipulation of the material.
Apply a range of concepts and principles in various contexts.
Use logical argument.
Demonstarte skilll in solving mathematical problems by various appropriate methods.
Problem-solving skills, relating qualitative and quantitative information.
Communication skills.
Numeracy and computational skills.
Time-management and organisational skills.

Notes

  1. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  2. The named convenor is the convenor for the current academic session.
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