Global optimization in the class of stochastically unimodal functions
Systems Analysis
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Abstract
Generalization of the global optimization problem based on a stochastic approach is considered. The concept of a stochastic (or unimodal in the mean) fuction is introduced. To find the optimal solution, a heuristic self-organization procedure is proposed.
Keywords
global optimization stochastically unimodal functions heuristic self-organizationPreview
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References
- 1.Kan A. H. G Rinnooy and G. T. Timmer, “Stochastic global optimization methods,” Math. Program., 39, No. 1, 27–56 (1987).MATHCrossRefGoogle Scholar
- 2.V. V. Moiseenko and V. V. Yatskevich, “Multiextremum optimization in a class of functions unimodal in the mean,” in: Proc. Int. Conf. Problems of Calculation Optimization [in Ukrainian], Kiev (1997), pp. 199–203.Google Scholar
- 3.J. Doob, Stochastic Processes [Russian translation], Izd. Inostr. Lit., Moscow (1956).Google Scholar
- 4.V. V. Yatskevich, “Description of optimization process accoriding to GMDH in terms of the theory of Markovian chains,” Avtomatika, No. 3, 92–95 (1988).Google Scholar
- 5.S. N. Trushin and V. V. Yatskevich, “A comparative analysis based on machine experiment of precise and approximated algorithms for determining the greatest internally stable set of a graph,” Kibernetika, No. 2, 111–112 (1985).Google Scholar
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