Archive for reference only

University Homepage
DRPS Homepage
DRPS Search
DRPS Contact
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. 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 for linear programs, non-linear programs and integer programs. Last, but not least, students are encouraged to use computer software for solving mathematical programs and to interpret computer output.
Course description The 4 main topics covered in this course are: Introduction to OR/MS and Model Building, Linear Programming, Integer Programming, Non-linear Programming.
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.

Course Delivery Information
Academic year 2014/15, Available to all students (SV1) Quota:  None
Course Start Semester 2
Timetable Timetable
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 )
Assessment (Further Info) Written Exam 70 %, Coursework 30 %, Practical Exam 0 %
Additional Information (Assessment) By one project (30%) and a final examination (70%).
Feedback Not entered
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S2 (April/May)2:00
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.

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 Not entered
Additional 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.
Keywordsmathematical programming, operational research, model building
Course organiserDr Jamal Ouenniche
Tel: (0131 6)50 3792
Course secretaryMs Patricia Ward-Scaltsas
Tel: (0131 6)50 3823
Help & Information
Search DPTs and Courses
Degree Programmes
Browse DPTs
Humanities and Social Science
Science and Engineering
Medicine and Veterinary Medicine
Other Information
Combined Course Timetable
Important Information
© Copyright 2014 The University of Edinburgh - 12 January 2015 3:33 am