| TAOP34 |
Large Scale Optimization, 6 ECTS credits.
/Optimering av stora system /
For:
I
Ii
M
MMAT
Y
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Prel. scheduled
hours: 64
Rec. self-study hours: 96
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Area of Education: Science
Main field of studies: Mathematics, Applied Mathematics,
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Advancement level
(G1, G2, A): A
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Aim:
The course aims at giving insight into the practical application of optimization methodology to technical and economic decision problems, and to give knowledge about solution principles for certain classes of structured large-scale optimization problems that frequently arise in practical applications. After the course, the student shall:
- be able to state and describe the mathematical principles that are used to decompose optimization problems
- be able to apply decomposition methods to solve structured optimization problems
- be acquainted with applications of decomposition methods, be able to identify applications that are well suited for such methods, and be able to choose a suitable methodology and use thereof
- have an enhanced knowledge of the practical use of optimization methodology.
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Prerequisites: (valid for students admitted to programmes within which the course is offered)
An introductory course in optimization.
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshhold requirements for progression within the programme, or corresponding.
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Supplementary courses:
Supply chain optimization.
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Organisation:
The lectures cover model building, theory, and solution methods for large-scale optimization, and give examples of applications. The participants in the course present solutions to assignments, which include numerical excercises, theoretical questions, and further applications. The laboratory exercises comprise the solution of specially structured optimization problems using standard computer software.
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Course contents:
Advanced linear programming and column generation. Price-directive decentralized planning and the Dantzig-Wolfe decomposition principle. Lagrangean relaxation and subgradient optimization. Application to problems arising in for example facility location and in the planning of production and distribution.
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Course literature:
Handouts.
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Examination: |
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Laboratory course and assignments.
Oral examination.
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1 ECTS
5 ECTS
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Course language is Swedish/English.
Department offering the course: MAI.
Director of Studies: Ingegerd Skoglund
Examiner: Torbjörn Larsson
Link to the course homepage at the department
Course Syllabus in Swedish
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