Сибирский федеральный университет

Тип публикации: статья из журнала

Год издания: 2020

Идентификатор DOI: 10.17223/19988605/50/6

Ключевые слова: global optimization, discrete variable, selective averaging of decision variables, multiextreme function, constraints of inequality type

Аннотация: In the paper, the functional of selective averaging of discrete decision variables is proposed. The positive selectivity coefficient is entered into a positive decreasing kernel of functional and with growth of selectivity coefficient the mean gives optimum values (in a limit) of decision discrete variables in a problem of global optimization. Based on the estimate of the selective averaging functional, a basic global optimization algorithm is synthesized on a set of discrete variables with ordered possible values under inequality constraints. The basis is a computational scheme for optimizing continuous variables and its transformation for optimization with respect to discrete variables. On a test example the high convergence rate and a noise stability of base algorithm are shown. Simulations have shown that the estimate of the probability of making a true decision reaches unit.

Журнал: VESTNIK TOMSKOGO GOSUDARSTVENNOGO UNIVERSITETA-UPRAVLENIE VYCHISLITELNAJA TEHNIKA I INFORMATIKA-TOMSK STATE UNIVERSITY JOURNAL OF CONTROL AND COMPUTER SCIENCE

Выпуск журнала: Is. 50

Номера страниц: 47-55

ISSN журнала: 19988605

Место издания: TOMSK

Издатель: TOMSK STATE UNIV

• Rouban A.I. (Siberian Fed Univ, Inst Space & Informat Technol, Tech Sci, Krasnoyarsk, Russia; Siberian Fed Univ, Inst Space & Informat Technol, Comp Sci Dept, Krasnoyarsk, Russia)
• Mikhalev A.A. (Siberian Fed Univ, Inst Space & Informat Technol, Krasnoyarsk, Russia)

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