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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 : School of Mathematics : Mathematics

Postgraduate Course: Fundamentals of Optimization (MATH11111)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Course typeStandard AvailabilityAvailable to all students
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) Credits10
Home subject areaMathematics Other subject areaNone
Course website https://info.maths.ed.ac.uk/teaching Taught in Gaelic?No
Course descriptionConvexity; 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.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed:
Co-requisites
Prohibited Combinations Other requirements None
Additional Costs None
Information for Visiting Students
Pre-requisitesNone
Displayed in Visiting Students Prospectus?Yes
Course Delivery Information
Delivery period: 2013/14 Semester 1, Not available to visiting students (SS1) Learn enabled:  Yes Quota:  None
Web Timetable Web Timetable
Course Start Date 19/09/2013
Breakdown of 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 )
Additional Notes
Breakdown of Assessment Methods (Further Info) Written Exam 80 %, Coursework 20 %, Practical Exam 0 %
Exam Information
Exam Diet Paper Name Hours:Minutes
Main Exam Diet S1 (December)Fundamentals of Optimization2:00
Summary of Intended 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.
Assessment Information
See 'Breakdown of Assessment Methods' and 'Additional Notes', above.
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus Not entered
Transferable skills Not entered
Reading list Not entered
Study Abroad Not entered
Study Pattern Not entered
KeywordsFuO
Contacts
Course organiserProf Kenneth Mckinnon
Tel: (0131 6)50 5042
Email: K.McKinnon@ed.ac.uk
Course secretaryMrs Frances Reid
Tel: (0131 6)50 4883
Email: f.c.reid@ed.ac.uk
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