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Algorithm for Extracting Multi-stage Structure from Sparse Optimisation Problems


G. Ulli

Semester Thesis, SS16 (10505)

In recent years, fast solvers have emerged that exploit the special multi-stage structure of optimisation problems associated with model predictive control. A common shortcoming of those solvers is that they cannot be used in connection with modelling languages like Yalmip. This thesis addresses this issue. It describes an algorithm that can extract the multi-stage structure from a general QCQP. This algorithm is then used in an interface connecting Yalmip with Forces Pro, a fast solver for multi-stage problems. It is demonstrated that using this interface for simple multi-stage QPs leads to solvers that are 9-40 times faster than standard Yalmip methods.

Supervisor: Alexander Domahidi, Juan Jerez, Andreas Hempel, Manfred Morari


Type of Publication:

(13)Semester/Bachelor Thesis

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2016:IFA_5475
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