Optimization of Algorithmic Parameters using a Meta-Control Approach* |
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Authors: | Wolf Kohn Zelda B Zabinsky Vladimir Brayman |
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Institution: | (1) Clearsight Systems Inc., Industrial Engineering, University of Washington, Bellevue, WA 98006, USA |
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Abstract: | Optimization algorithms usually rely on the setting of parameters, such as barrier coefficients. We have developed a generic
meta-control procedure to optimize the behavior of given iterative optimization algorithms. In this procedure, an optimal
continuous control problem is defined to compute the parameters of an iterative algorithm as control variables to achieve
a desired behavior of the algorithm (e.g., convergence time, memory resources, and quality of solution). The procedure is
illustrated with an interior point algorithm to control barrier coefficients for constrained nonlinear optimization. Three
numerical examples are included to demonstrate the enhanced performance of this method.
This work was primarily done when Z. Zabinsky was visiting Clearsight Systems Inc. |
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Keywords: | Algorithms Interior-point Nonlinear Optimization Optimal Control |
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