Postgraduate Course: Fundamentals of Optimization (MATH11111)
Course Outline
| School | School of Mathematics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | Convexity; Linear Programming: model formulation, simplex method (SM): tableau form, revised SM, geometric interpretation, sensitivity analysis; Extensions and applications of LP: goal programming, data envelopment analysis (DEA), network optimization problems, piecewise linear objective, cutting plane methods; Duality in LP, Lagrangian Relaxation; Solving LP problems using commercial mathematical programming software; Public domain software for optimization, NEOS. |
| Course description |
Not entered
|
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
Students MUST have passed:
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
|
| Academic year 2015/16, Not available to visiting students (SS1)
|
Quota: None |
| Course Start |
Semester 1 |
| Course Start Date |
21/09/2015 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 22,
Seminar/Tutorial Hours 12,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
62 )
|
| Assessment (Further Info) |
Written Exam
80 %,
Coursework
20 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
See 'Breakdown of Assessment Methods' and 'Additional Notes', above. |
| Feedback |
Not entered |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S1 (December) | MATH11111 Fundamentals of Optimization | 2:00 | |
Learning Outcomes
| Knowledge of basic optimization techniques. Ability to formulate decision problems as optimization problems. Ability to solve simple problems and to use the right software to solve complicated problems.
|
Contacts
| Course organiser | Prof Jacek Gondzio
Tel: (0131 6)50 8574
Email: J.Gondzio@ed.ac.uk |
Course secretary | Mrs Frances Reid
Tel: (0131 6)50 4883
Email: f.c.reid@ed.ac.uk |
|
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