Practical & Large Scale Optimization (U01881)

? Credit Points : 10 ? SCQF Level : 11 ? Acronym : MAT-4-PLO

Course for final year students in Honours programmes in Mathematics.

Implementation of the revised simplex method; interior point methods for linear, quadratic and nonlinear optimization; sparse matrix techniques in optimization; decomposition methods: Benders and Dantzig-Wolfe decompositions; Newton method, self-concordant barriers, semidefinite programming; applications of mathematical programming in finance and telecommunications.

Entry Requirements

? Pre-requisites : Passes at C or better in (MAT-2-FoC, MAT-2-SVC, MAT-2-LiA, MAT-2-MAM) or (MAT-2-am3, MAT-2-mm3, MAT-2-am4, MAT-2-mm4 with permission of the Head of School) or (MAT-2-mi3, MAT-2-mi4 with permission of Head of School)

Subject Areas

Home subject area

Specialist Mathematics & Statistics (Honours), (School of Mathematics, Schedule P)

Delivery Information

? Normal year taken : 4th year

? Delivery Period : Semester 2 (Blocks 3-4)

? Contact Teaching Time : 2 hour(s) per week for 11 weeks

First Class Information

Date	Start	End	Room	Area	Additional Information
13/01/2009	10:00	10:50	Lecture Room 3317, JCMB	KB

All of the following classes

Type	Day	Start	End	Area
Lecture	Tuesday	10:00	10:50	KB
Lecture	Friday	10:00	10:50	KB

Summary of Intended Learning Outcomes

1. Understanding of practical methods of large-scale optimization and their modern implementations.
2. Awareness of the practical complexity of the problems.
3. Ability to model real-life problems as optimization problems.
4. Ability to develop and implement an optimization technique.