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A New Algorithm for Global Minimization Based on the Combination of Adaptive Random Search and Simplex Algorithm of Nelder and Mead

Miljenko Huzak ; Department of Mathematics, University of Zagreb, Bijenička 30, 10000 Zagreb, Croatia
Željko Bajzer ; Department of Biochemistry and Molecular Biology, Mathematical Methods Core Facility, Maya Foundation, Rochester MN, 55905

Sažetak

We propose a new general-purpose algorithm for locating global
minima of differentiable and nondifferentiable multivariable functions.
The algorithm is based on combination of the adaptive random
search approach and the Nelder-Mead simplex minimization.
We show that the new hybrid algorithm satisfies the conditions of
the theorem for convergence (in probability) to global minimum. By
using test functions we demonstrate that the proposed algorithm
is far more efficient than the pure adaptive random search algorithm,
Some of the considered test functions are related to membership
set estimation method for model parameter determination which was successfully applied to kinetic problems in chemistry and biology.

Ključne riječi

Hrčak ID:

177110

URI

https://hrcak.srce.hr/177110

Datum izdavanja:

1.11.1996.

Posjeta: 1.047 *