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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2013/2014 -
- ARCHIVE as at 1 September 2013 for reference only
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DRPS : Course Catalogue : Business School : Business Studies

Undergraduate Course: Mathematical Programming (BUST10011)

Course Outline
SchoolBusiness School CollegeCollege of Humanities and Social Science
Course typeStandard AvailabilityAvailable to all students
Credit level (Normal year taken)SCQF Level 10 (Year 3 Undergraduate) Credits20
Home subject areaBusiness Studies Other subject areaNone
Course website None Taught in Gaelic?No
Course descriptionOptimisation in networks: flows in networks, shortest routes, spanning trees. Integer programming: problem formulations and methods of model solution. The concepts of branch and bound and related strategies. Applications in distribution, production, investment, communications.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Management Science and Information Systems (BUST08007) OR Management Science and Operations Planning (BUST10020)
Co-requisites
Prohibited Combinations Other requirements Note: For Economics with Management Science, and Mathematics and Business Studies programmes EITHER Mathematical Programming OR Decision Making Under Uncertainty (BUST10013) is a mandatory course in Year 4.
Additional Costs None
Information for Visiting Students
Pre-requisitesA pass in Management Science and Information Systems (BUST08007) OR
Management Science and Operations Planning (BUST10020) equivalents.

Visiting students should have at least 3 Business Studies courses at grade B or above (or be predicted to obtain this). We will only consider University/College level courses.


Displayed in Visiting Students Prospectus?Yes
Course Delivery Information
Delivery period: 2013/14 Semester 2, Available to all students (SV1) Learn enabled:  Yes Quota:  None
Web Timetable Web Timetable
Class Delivery Information There will be four x two-hour non-compulsory tutorials 4.10-6pm on Thursdays in Weeks 2,5,9 and 11 (23 January, 13 February, 13 March and 27 March), in Faculty Room North, David Hume Tower.
Course Start Date 13/01/2014
Breakdown of Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 20, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 174 )
Additional Notes
Breakdown of Assessment Methods (Further Info) Written Exam 70 %, Coursework 30 %, Practical Exam 0 %
Exam Information
Exam Diet Paper Name Hours:Minutes
Main Exam Diet S2 (April/May)2:00
Summary of Intended Learning Outcomes
Objective/Learning Outcomes

Knowledge and Understanding

On completion of the course students should:
(i) be able to assess critically the utility of a number of mathematical programming techniques
(ii) be able to describe mathematical programming solution techniques
(iii) be able to use mathematical programming methods to model management decision problems.

Cognitive Skills

On completion of the course students should:
(i) demonstrate ability in deciding whether a problem is amenable to solution by mathematical programming techniques
(ii) demonstrate ability in using mathematical programming solution techniques
(iii) demonstrate ability in explaining the solution to mathematical programming models.

Key Skills

On completion of the course students should:
(i) be able to formulate problems in mathematical programming terms
(ii) be able to solve mathematical programming problems using commercial software.
(iii) be able to communicate mathematical programming solutions to non-specialists.

Subject Specific Skills

On completion of the course students should:
(i) have extended their model building skills
(ii) have increased their model solution skills.

Assessment Information
By one project (30%) and a final examination (70%).
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus The 4 main topics covered in this course are: Introduction to OR/MS and Model Building, Linear Programming, Integer Programming, Non-linear Programming.
Transferable skills Not entered
Reading list Recommended Reading:
1. S. P. Bradley, A. C. Hax, and T. L. Magnanti (1977), Applied Mathematical Programming, Addison-Wesley. [JCM Library shelfmark QA402.5 Bra; copy on order for Main Library HUB Reserve};
2. M. S. Bazaraa, H. D. Sherali, C. M. Shetty (2006), Nonlinear Programming: Theory and Algorithms, third edition, Wiley. [Copy in Main Library HUB Reserve shelfmark T57.8 Baz].
Study Abroad Not entered
Study Pattern Not entered
KeywordsMP
Contacts
Course organiserDr Jamal Ouenniche
Tel: (0131 6)50 3792
Email: Jamal.Ouenniche@ed.ac.uk
Course secretaryMs Patricia Ward-Scaltsas
Tel: (0131 6)50 3823
Email: Patricia.Ward-Scaltsas@ed.ac.uk
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