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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
Credit level (Normal year taken)SCQF Level 10 (Year 3 Undergraduate) AvailabilityAvailable to all students
SCQF Credits20 ECTS Credits10
SummaryOptimisation problems are concerned with optimising an objective function subject to a set of constraints. When optimisation problems are translated in algebraic form, we refer to them as mathematical programs. Mathematical programming, as an area within Operational Research / Management Science (OR/MS), is concerned with strategies and methods for solving mathematical programs.
Course description In this course, we address model building and validation in OR/MS, present a variety of typical OR/MS problems and their formulations, provide general tips on how to model certain managerial situations, and discuss solution strategies and present solution methods. Students are encouraged to use computer software for solving mathematical programs and to interpret computer output.

1. Introduction to OR/MS and Model Building
2. Linear Programming
3. Integer Programming
4. Non-linear Programming.

Student Learning Experience
The lecture programme, which builds on knowledge from Management Science courses in earlier years, develops mathematical programming model-building and solution techniques, and is supported by recommended reading and tutorials. Tutorials provide opportunities to gain experience in using techniques and to discuss alternative formulations. Students are required to complete a project.
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)
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.
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.

High Demand Course? Yes
Course Delivery Information
Not being delivered
Learning Outcomes
On completion of this course, the student will be able to:
  1. Assess critically the utility of a number of mathematical programming techniques.
  2. Describe mathematical programming solution techniques.
  3. Use mathematical programming methods to model and solve management decision problems.
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].
Additional Information
Graduate Attributes and Skills 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.
Additional Class Delivery Information There will be one 2-hour lecture per week on Wednesdays 9.00-10.50am and four x 2-hour non-compulsory tutorials 4.10-6pm on Thursdays in Weeks 2, 4, 5 and 11.
Course organiserProf Jamal Ouenniche
Tel: (0131 6)50 3792
Course secretaryMs Patricia Ward-Scaltsas
Tel: (0131 6)50 3823
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