FMINDEMO optimization cross-comparison A systematic test of all optimization methods is performed using a set of test problems. Starting configurations are chosen randomly. The option flag may contain the following keywords: 'verbose' displays individual detailed optimization results. 'rand' adds a 10% gaussian random noise to all functions The test can be repeated iteratively so that a Monte Carlo sampling of starting parameters give a better stastistical estimate of each method efficiency. Calling: fmindemo(dimensionality=vector, option='verbose, rand', repetitions) Example: fmindemo([ 2 10 50],1) % detailed test with 2,5 and 10 parameters fmindemo(2,[], 10) % 2 parameters optimization repeated 10 times Contrib: Test functions from Nikolaus Hansen, 2001-2007. e-mail: hansen@bionik.tu-berlin.de (c) E.Farhi, ILL. License: EUPL.

- fmindemo FMINDEMO optimization cross-comparison

- fmindemo FMINDEMO optimization cross-comparison

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