Module: Optimisation

Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title	Optimisation
Module Code	MS434
School	School of Mathematical Sciences
Module Co-ordinator	Semester 1: Thomas Brady Semester 2: Thomas Brady Autumn: Thomas Brady
Module Teachers	Thomas Brady
NFQ level	8	Credit Rating	7.5
Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

None

Description

This module provides an introduction to combinatorial optimisation. In this module students will develop knowledge and skills in the basic combinatorial algorithms applied to optimisation. The participants are expected to have a good knowledge of linear algebra and experience with the abstract approach to mathematics. This module provides the first steps in the discipline known as operations research. Students are expected to attend lectures, participate in tutorials and take in-class tests.

Learning Outcomes

1. Apply algorithms in optimisation problems
2. Demonstrate a knowledge of the geometry underlying linear programming
3. Interpret algorithm output
4. Construct proofs of simple propositions

*Type*	*Hours*	*Description*
Workload	Full-time hours per semester
Lecture	36	Lecture
Tutorial	12	Tutorial
Independent Study	170	Independent earning
Directed learning	2	Final Exam
Total Workload: 220

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Graphs
Graphs, trees, shortest path algorithms, greedy algorithm, matroids

Polytopes
Polytopes, Farkas' Lemma, linear programming, the geometry of linear inequalities

Matchings
matching problems, bipartite matching, weighted matching

Network flow
max-flow via simplex method, and via graph search

Assessment Breakdown
Continuous Assessment	20%	Examination Weight	80%

Type	Description	% of total	Assessment Date
Course Work Breakdown
In Class Test	In Class test	20%	Every Second Week

Reassessment Requirement Type
Resit arrangements are explained by the following categories; 1 = A resit is available for all components of the module 2 = No resit is available for 100% continuous assessment module 3 = No resit is available for the continuous assessment component
This module is category 3

Indicative Reading List

Eugene Lawler: 2001, Combinatorial optimization, Dover Publications, Mineola, N.Y., 0486414531
Hamdy A. Taha,: 2010, Operations Research: An Introduction, 9th, Prentice-Hall, 9780132555937

Other Resources

None

Programme or List of Programmes

ACM	BSc in Actuarial Mathematics
FIM	B.Sc. Financial Mathematics

Archives: