IØ8803

Stochastic Programming, module 2

Last taught 2015

Autumn

English

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About this course

Content

Stochastic Programming, module 2 is an intensive PhD course over 3 days given by Professor Csaba I. Fábián, Kecskemét College, Hungary. Course content includes: Overview of linear and convex programming methods Well-known static models, problems and their solution Two-stage models with recourse. Problems and methods

Learning outcomes

The course will provide knowledge within solution methodology of two-stage stochastic programs, emphasizing cutting plane methods. At the end of the course, students are expected to discuss and explain when different methods are useful, i.e. for which problem classes the various methods can be advantageously used. Students are expected to be able to recognize which problem class a given stochastic programming problem belongs to. Further, they are expected to be able to implement various forms of risk aversion in stochastic programming applications they are working on.

Teaching methods

Lectures and problem solving sessions.