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Benchmarking Derivative Free Optimization Algorithms
Joey Reed
Department of Mathematics
UCSD
Abstract
With increasingly complex optimization problems to solve, the
availiability and computability of derivatives becomes unreasonable. As a
result, it is important to test the quality of different optimization
algorithms which do not use derivative information. We present a small
benchmarking collection for direct search algorithms. All implementation
has been done in MATLAB. This work was joint with Jorge More of Argonne
National Lab.
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