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Statistical and numerical algorithms, Scientific Research and Discoveries, Control Systems and Identification

A Simplex Method for Function Minimization

The Computer Journal · 1965

JJ. A. Nelder·RR. Mead
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Abstract

A method is described for the minimization of a function of n variables, which depends on the comparison of function values at the (n + 1) vertices of a general simplex, followed by the replacement of the vertex with the highest value by another point. The simplex adapts itself to the local landscape, and contracts on to the final minimum. The method is shown to be effective and computationally compact. A procedure is given for the estimation of the Hessian matrix in the neighbourhood of the minimum, needed in statistical estimation problems.

Research topics

Control Systems and IdentificationScientific Research and DiscoveriesStatistical and numerical algorithms
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