Constraint Reduction for Linear and Convex OptimizationAndre L. Tits
Department of Electrical and Computer Engineering, University of Maryland
Tuesday, March 11, 2014 15:30-16:30,
Constraint reduction is a technique by which, in the context of interior-point methods for the solution of optimization problems, at each iteration, the search direction computation involves only a small subset of the inequality constraints. For problems with many more constraints than variables, this can yield a dramatic speedup. We provide some background, outline schemes, discuss convergence properties, and report numerical results, both on randomly generated problems and on problems arising in specific applications.
Contact: A. Gueye
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