Automated, Parallel Optimization of Stochastic Functions Using a Modified Simplex Algorithm

This paper proposes a framework and new parallel algorithm for optimization of stochastic functions based on a downhill simplex algorithm. The function to be optimized is assumed to be subject to random noise, the variance of which decreases with sampling time, this is the situation expected for man...

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Veröffentlicht in:	2010 Sixth IEEE International Conference on E-Science Workshops S. 98 - 103
Hauptverfasser:	Chahal, D, Stuart, S J, Goasguen, S, Trout, C J
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.12.2010
Schlagworte:	Computational modeling Noise Noise measurement Object oriented modeling Optimization parallel optimizaton Servers simplex Stochastic processes water model
ISBN:	9781424489886, 1424489881
Online-Zugang:	Volltext
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