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Evaluation of Different Bilevel Optimization Algorithms with Applications to Control


Ivana Rauova

Master Thesis FS 10 (10026)

Bilevel optimization problems are optimization problems where parts of the constraints are in the form that some variables in the problem (the upper level problem) are constrained to be optimal solutions to another optimization problem (the lower level problem). These problems are in most cases non-convex and therefore hard to solve to global optimality. Recently, it has been discovered that these problem formulations can be very useful in automatic control applications. For example, they can be used to compute the worst case deviation of a suboptimal Model Predictive Control scheme compared to the optimal one. The objective with this work is to compare different bilevel optimization algorithms where the comparison is performed both theoretically and numerically. The most important properties compared are if the algorithms can find a global optimizer guaranteed, the numerical robustness (as observed in numerical experiments), and the computational performance.


Type of Publication:

(12)Diploma/Master Thesis

C.N. Jones

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2010:IFA_4107
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