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Benchmarking Derivative Free Optimization Algorithms

Joey Reed
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.

Tuesday, October 14, 2008
11:00AM AP&M 2402