0x010088F6312065A70A44B630A6848498EAD80093CFEAFE161DC94D83C7C5C9A5A748B8

Completely reshaped the course. Changed from colloquium-based course to one-week intensive course based on lectures from various lecturers.

The course went well generally. Students were happy with the content, will try to ask mostly the same guest lecturers next time.Students were generally happy with the lecturers.Some requests to move julia implementation to the first course; otherwise cut down on time spent there.Students especially appreciate practical questions in between theoretical lecturing. Will try to add more of that in risk-averse and DRO lectures.Should try to structure the week a bit more.We haven't graded the exam yet, so no comment there.

Scheduling was somewhat chaotic (finding rooms, finding guest lecturers). Will start planning earlier this year.Otherwise, everything went well.

NTNU:TIA:REST

Institutt for industriell økonomi og teknologiledelse

Department of Industrial Economics and Technology Management

Engelsk

Anbefalte forkunnskaper

Knowledge of linear and nonlinear optimization is essential. Such knowledge can be obtained through courses TIØ4120 Operations Research, Introduction, TIØ4126 Optimization and Decision Support for Industrial Business Planning, or TIØ4130 Optimization Methods with Applications, or similar. The course builds on the PhD course IØ8403 Stochastic Optimization.

Faglig innhold

The course provides knowledge of methods and models for optimization based decision support under uncertainty and risk. The course consists of four related parts:<ul><li>Theory</li><li>Decomposition Algorithms</li><li>Advanced models</li><li>Scenario generation</li></ul>

Kursmateriell

Læringsutbytte

The course is designed for PhD students who work with theoretical and practical optimization problems under uncertainty, in industry and services.The course will convey the following knowledge: The theoretical foundation necessary for formulation, analysis and solution of stochastic programming problems and relevant applications. The knowledge necessary to conduct research in the field of optimization under uncertainty. The course builds on and extends IØ8403 Stochastic Optimization, focusing more on advanced models, decomposition algorithms and scenario generation.The course will develop the following skills: Training to build and solve optimization models for solution of planning and economic problems under uncertainty in energy, production, logistics, transportation, finance, telecom.

Læringsformer og aktiviteter

Lectures and exercises. Non-obligatory exercises. The course can be given in form of intensive lectures with several hours per day, several days per week, during a limited number of weeks in the semester.

Avansert optimering under usikkerhet

Bedriftsøkonomi og optimering

Industriell økonomi og teknologiledelse

Bedriftsøkonomi

Operasjonsanalyse

Økonomi og ledelse - doktorgrad (ph.d.)

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Avansert optimering under usikkerhet - IØ8404