Abstract
Appearance of multiprocessor computer systems and local computer networks gives wide latitude for constructing optimization techniques using parallel iterations including simultaneous (due to many processors) computations (trials) of function to be optimized values at several points in a parameter space. Each trial appearing in sach parallel iteration could be performed at a separate processing unit using the same (shared or copied) program.
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References
Strongin, R.G. (1978) Numerical Methods in Multiextremal Problems. Nauka, Moscow (in Russian)
Strongin, R.G. (1985) Numerical Methods for Multiextremal Nonlinear Programming Problems with Nonconvex Constraints. In Lecture Notes in Economics and Mathematical Systems, vol.255, pp.278–282. Proceedings 1984. Edited by V. F.Demyanov and D.Pallaschke. Springer-Verlag. Berl in Heidelberg
Strongin, R.G., Markin, D.L. (1986) Minimization of Multiextremal Functions with Nonconvex Constraints. Kibernetika, (4): 64–69 (in Russian)
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© 1988 Springer-Verlag Berlin Heidelberg
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Strongin, R.G., Sergeev, Y.D. (1988). Effective Algoritm for Global Optimization with Parallel Computations. In: Kurzhanski, A., Neumann, K., Pallaschke, D. (eds) Optimization, Parallel Processing and Applications. Lecture Notes in Economics and Mathematical Systems, vol 304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-46631-1_13
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DOI: https://doi.org/10.1007/978-3-642-46631-1_13
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