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Original scientific paper

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

Fulltext: english, pdf (6 MB) pages 775-791 downloads: 184* cite
APA 6th Edition
Huzak, M. & Bajzer, Ž. (1996). A New Algorithm for Global Minimization Based on the Combination of Adaptive Random Search and Simplex Algorithm of Nelder and Mead. Croatica Chemica Acta, 69 (3), 775-791. Retrieved from https://hrcak.srce.hr/177110
MLA 8th Edition
Huzak, Miljenko and Željko Bajzer. "A New Algorithm for Global Minimization Based on the Combination of Adaptive Random Search and Simplex Algorithm of Nelder and Mead." Croatica Chemica Acta, vol. 69, no. 3, 1996, pp. 775-791. https://hrcak.srce.hr/177110. Accessed 25 Jul. 2021.
Chicago 17th Edition
Huzak, Miljenko and Željko Bajzer. "A New Algorithm for Global Minimization Based on the Combination of Adaptive Random Search and Simplex Algorithm of Nelder and Mead." Croatica Chemica Acta 69, no. 3 (1996): 775-791. https://hrcak.srce.hr/177110
Harvard
Huzak, M., and Bajzer, Ž. (1996). 'A New Algorithm for Global Minimization Based on the Combination of Adaptive Random Search and Simplex Algorithm of Nelder and Mead', Croatica Chemica Acta, 69(3), pp. 775-791. Available at: https://hrcak.srce.hr/177110 (Accessed 25 July 2021)
Vancouver
Huzak M, Bajzer Ž. A New Algorithm for Global Minimization Based on the Combination of Adaptive Random Search and Simplex Algorithm of Nelder and Mead. Croatica Chemica Acta [Internet]. 1996 [cited 2021 July 25];69(3):775-791. Available from: https://hrcak.srce.hr/177110
IEEE
M. Huzak and Ž. Bajzer, "A New Algorithm for Global Minimization Based on the Combination of Adaptive Random Search and Simplex Algorithm of Nelder and Mead", Croatica Chemica Acta, vol.69, no. 3, pp. 775-791, 1996. [Online]. Available: https://hrcak.srce.hr/177110. [Accessed: 25 July 2021]

Abstracts
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.

Hrčak ID: 177110

URI
https://hrcak.srce.hr/177110

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