Undergraduate Course: Mathematical Programming (BUST10011)
Course Outline
| School | Business School |
College | College of Humanities and Social Science |
| Credit level (Normal year taken) | SCQF Level 10 (Year 3 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | Optimisation 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.
Syllabus
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.
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Information for Visiting Students
| Pre-requisites | A 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.
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| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2015/16, Available to all students (SV1)
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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 )
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| Assessment (Further Info) |
Written Exam
70 %,
Coursework
30 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Coursework (30%): one individual project including a 1000-word report along with an excel file.
Final Examination (70%).
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| Feedback |
1. Generic feedback on your COURSEWORK, together with individual marks, will be posted on Learn within 15 working days from the submission deadline; also the individual feedback for your coursework will be available to collect from the Business Studies Office (Room 1.11, Business School, 29 Buccleuch Place), but you will not be able to take away the original piece of coursework, as it may be required by the Board of Examiners.
2. The non-compulsory tutorials provide further opportunity for doing exercises and asking questions.
3. Your EXAMINATION marks will be posted on Learn (together with generic feedback and examination statistics) as soon as possible after the April/May Diet Board of Examiners' meeting (normally early-mid JUNE). During the summer months (i.e. mid/end June - end August), you may come into the Business Studies Office (Room 1.11, Business School, 29 Buccleuch Place) to look at your examination scripts. Note that you will not be able to remove any examination scripts from the UG Office as they may be required by the Board of Examiners.
Continuing students will also be given the opportunity to review their examination scripts early in the new academic year in Semester 1 (i.e. in October).
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| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
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| Main Exam Diet S2 (April/May) | | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- Assess critically the utility of a number of mathematical programming techniques.
- Describe mathematical programming solution techniques.
- Use mathematical programming methods to model and solve management decision problems.
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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].
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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.
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| Additional Class Delivery Information |
There will be one 2-hour lecture per week on Wednesdays 9.00-10.50am and four x two-hour non-compulsory tutorials 4.10-6pm on Thursdays in Weeks 2,5,9 and 11. |
| Keywords | MP |
Contacts
| Course organiser | Dr Jamal Ouenniche
Tel: (0131 6)50 3792
Email: Jamal.Ouenniche@ed.ac.uk |
Course secretary | Ms Patricia Ward-Scaltsas
Tel: (0131 6)50 3823
Email: Patricia.Ward-Scaltsas@ed.ac.uk |
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