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Acceleration procedure for special classes of multi-extremal problems. / Bykadorov, Igor.

In: Optimization Letters, Vol. 13, No. 8, 01.11.2019, p. 1819-1835.

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Bykadorov I. Acceleration procedure for special classes of multi-extremal problems. Optimization Letters. 2019 Nov 1;13(8):1819-1835. doi: 10.1007/s11590-018-1355-6

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Bykadorov, Igor. / Acceleration procedure for special classes of multi-extremal problems. In: Optimization Letters. 2019 ; Vol. 13, No. 8. pp. 1819-1835.

BibTeX

@article{74cdc1210f464a75bc738a217c2a9840,
title = "Acceleration procedure for special classes of multi-extremal problems",
abstract = "We suggest an approach to solve special classes of multi-extreme problems to optimize the combination (e.g., sum, product) of several functions, under the assumption that the effective algorithms to optimize each of this item are known. The algorithm proposed is iterative. It realizes one of the idea of the branch-and-bound method and consists in successive correcting of the low and the upper bounds of optimal value of objective functions. In each iteration, the total area of the considered region that may contain the image optimal point, decreases at least twice. Various techniques that accelerate the process of finding solutions are discussed.",
keywords = "Generalized concavity, Global optimization, Multi-extremal problems",
author = "Igor Bykadorov",
year = "2019",
month = nov,
day = "1",
doi = "10.1007/s11590-018-1355-6",
language = "English",
volume = "13",
pages = "1819--1835",
journal = "Optimization Letters",
issn = "1862-4472",
publisher = "Springer-Verlag GmbH and Co. KG",
number = "8",

}

RIS

TY - JOUR

T1 - Acceleration procedure for special classes of multi-extremal problems

AU - Bykadorov, Igor

PY - 2019/11/1

Y1 - 2019/11/1

N2 - We suggest an approach to solve special classes of multi-extreme problems to optimize the combination (e.g., sum, product) of several functions, under the assumption that the effective algorithms to optimize each of this item are known. The algorithm proposed is iterative. It realizes one of the idea of the branch-and-bound method and consists in successive correcting of the low and the upper bounds of optimal value of objective functions. In each iteration, the total area of the considered region that may contain the image optimal point, decreases at least twice. Various techniques that accelerate the process of finding solutions are discussed.

AB - We suggest an approach to solve special classes of multi-extreme problems to optimize the combination (e.g., sum, product) of several functions, under the assumption that the effective algorithms to optimize each of this item are known. The algorithm proposed is iterative. It realizes one of the idea of the branch-and-bound method and consists in successive correcting of the low and the upper bounds of optimal value of objective functions. In each iteration, the total area of the considered region that may contain the image optimal point, decreases at least twice. Various techniques that accelerate the process of finding solutions are discussed.

KW - Generalized concavity

KW - Global optimization

KW - Multi-extremal problems

UR - http://www.scopus.com/inward/record.url?scp=85056577081&partnerID=8YFLogxK

U2 - 10.1007/s11590-018-1355-6

DO - 10.1007/s11590-018-1355-6

M3 - Article

AN - SCOPUS:85056577081

VL - 13

SP - 1819

EP - 1835

JO - Optimization Letters

JF - Optimization Letters

SN - 1862-4472

IS - 8

ER -

ID: 17488378