Academic Year: 
2014/5 
Owning Department/School: 
Department of Mathematical Sciences 
Credits: 
6 
Level: 
Honours (FHEQ level 6) 
Period: 
Semester 1

Assessment Summary: 
EX 100% 
Assessment Detail:  
Supplementary Assessment: 
MA30087 Mandatory extra work (where allowed by programme regulations)

Requisites: 
Before taking this unit you must take MA10207 and take MA10210 
Description: 
Aims & Learning Objectives:
Aims: To present methods of optimisation commonly used in OR, to explain their theoretical basis and give an appreciation of the variety of areas in which they are applicable.
Objectives:
On completing the course, students should be able to
* Recognise practical problems where optimisation methods can be used effectively
* Implement appropriate algorithms, and understand their procedures
* Understand the underlying theory of linear programming problems, especially duality.
Content: The Nature of OR: Brief introduction.
Linear Programming: Basic solutions and the fundamental theorem. The simplex algorithm, two phase method for an initial solution. Interpretation of the optimal tableau. Applications of LP. Duality.
Topics selected from:
Sensitivity analysis and the dual simplex algorithm. Brief discussion of Karmarkar's method. The transportation problem and its applications, solution by Dantzig's method. Network flow problems, the FordFulkerson theorem.
Nonlinear Programming: Revision of classical Lagrangian methods. KuhnTucker conditions, necessity and sufficiency. Illustration by application to quadratic programming.

Programme availability: 
MA30087 is Optional on the following programmes:
Department of Biology & Biochemistry
Department of Computer Science
 USCMAFB20 : BSc(Hons) Computer Science and Mathematics (Year 3)
 USCMAAB20 : BSc(Hons) Computer Science and Mathematics with Study year abroad (Year 4)
 USCMAKB20 : BSc(Hons) Computer Science and Mathematics with Year long work placement (Year 4)
 USCMAAB14 : BSc(Hons) Computer Science with Mathematics with Study year abroad (Year 4)
 USCMAKB14 : BSc(Hons) Computer Science with Mathematics with Year long work placement (Year 4)
 USCMAFB01 : BSc Computing (Year 3)
 USCMAKB01 : BSc Computing with Year long work placement (Year 4)
Department of Mathematical Sciences
 RSMAAFM16 : Integrated PhD in Statistical Applied Mathematics
 USMAAFB15 : BSc(Hons) Mathematical Sciences (Year 3)
 USMAAAB16 : BSc(Hons) Mathematical Sciences with Study year abroad (Year 4)
 USMAAKB16 : BSc(Hons) Mathematical Sciences with Year long work placement (Year 4)
 USMAAFB13 : BSc(Hons) Mathematics (Year 3)
 USMAAAB14 : BSc(Hons) Mathematics with Study year abroad (Year 4)
 USMAAKB14 : BSc(Hons) Mathematics with Year long work placement (Year 4)
 USMAAFM14 : MMath(Hons) Mathematics (Year 3)
 USMAAFM14 : MMath(Hons) Mathematics (Year 4)
 USMAAAM15 : MMath(Hons) Mathematics with Study year abroad (Year 4)
 USMAAKM15 : MMath(Hons) Mathematics with Year long work placement (Year 4)
 USMAAKM15 : MMath(Hons) Mathematics with Year long work placement (Year 5)
 USMAAFB01 : BSc(Hons) Mathematics and Statistics (Year 3)
 USMAAAB02 : BSc(Hons) Mathematics and Statistics with Study year abroad (Year 4)
 USMAAKB02 : BSc(Hons) Mathematics and Statistics with Year long work placement (Year 4)
 TSMAAFM17 : MRes Statistical Applied Mathematics
 TSMAAFM09 : MSc Mathematical Sciences
 TSMAAPM09 : MSc Mathematical Sciences
 TSMAAFM08 : MSc Modern Applications of Mathematics
 TSMAAWM14 : MSc Modern Applications of Mathematics
 TSMAAFM16 : MSc Statistical Applied Mathematics
 TSMAAFL02 : PG Dip Modern Applications of Mathematics
 USMAAFB05 : BSc(Hons) Statistics (Year 3)
 USMAAAB06 : BSc(Hons) Statistics with Study year abroad (Year 4)
 USMAAKB06 : BSc(Hons) Statistics with Year long work placement (Year 4)
Department of Physics
 USXXAFB03 : BSc(Hons) Mathematics and Physics (Year 3)
 USXXAAB04 : BSc(Hons) Mathematics and Physics with Study year abroad (Year 4)
 USXXAKB04 : BSc(Hons) Mathematics and Physics with Year long work placement (Year 4)
 USXXAFM01 : MSci(Hons) Mathematics and Physics (Year 4)
