Standard

Genetic algorithm for the resource-constrained project scheduling problem. / Goncharov, E. N.; Leonov, V. V.

в: Automation and Remote Control, Том 78, № 6, 01.06.2017, стр. 1101-1114.

Результаты исследований: Научные публикации в периодических изданияхстатьяРецензирование

Harvard

Goncharov, EN & Leonov, VV 2017, 'Genetic algorithm for the resource-constrained project scheduling problem', Automation and Remote Control, Том. 78, № 6, стр. 1101-1114. https://doi.org/10.1134/S0005117917060108

APA

Vancouver

Goncharov EN, Leonov VV. Genetic algorithm for the resource-constrained project scheduling problem. Automation and Remote Control. 2017 июнь 1;78(6):1101-1114. doi: 10.1134/S0005117917060108

Author

Goncharov, E. N. ; Leonov, V. V. / Genetic algorithm for the resource-constrained project scheduling problem. в: Automation and Remote Control. 2017 ; Том 78, № 6. стр. 1101-1114.

BibTeX

@article{a09f7771a8b54331b460bf6437f69fa1,
title = "Genetic algorithm for the resource-constrained project scheduling problem",
abstract = "We consider the resource-constrained project scheduling problem with respect to the makespan minimization criterion. The problem accounts for technological constraints of activities precedence together with resource constraints. We propose a genetic algorithm with two versions of crossovers based on the idea of most rational use of constrained resources. The crossovers uses a heuristic that takes into account the degree of criticality for the resources, which is derived from the solution of a relaxed problem with a constraint on accumulative resources. A numerical experiment with examples from the PCPLIB library has shown that the proposed algorithm has competitive quality. For some examples from the j120 test series the best known solutions were improved and for j60 (50 000 and 500 000 iterations) and for j120 (500 000 iterations) we have obtain the best average deviations of the solutions from the critical path value.",
keywords = "genetic algorithms, PCPLIB, renewable resources, resource-constrained project scheduling problem",
author = "Goncharov, {E. N.} and Leonov, {V. V.}",
year = "2017",
month = jun,
day = "1",
doi = "10.1134/S0005117917060108",
language = "English",
volume = "78",
pages = "1101--1114",
journal = "Automation and Remote Control",
issn = "0005-1179",
publisher = "Maik Nauka-Interperiodica Publishing",
number = "6",

}

RIS

TY - JOUR

T1 - Genetic algorithm for the resource-constrained project scheduling problem

AU - Goncharov, E. N.

AU - Leonov, V. V.

PY - 2017/6/1

Y1 - 2017/6/1

N2 - We consider the resource-constrained project scheduling problem with respect to the makespan minimization criterion. The problem accounts for technological constraints of activities precedence together with resource constraints. We propose a genetic algorithm with two versions of crossovers based on the idea of most rational use of constrained resources. The crossovers uses a heuristic that takes into account the degree of criticality for the resources, which is derived from the solution of a relaxed problem with a constraint on accumulative resources. A numerical experiment with examples from the PCPLIB library has shown that the proposed algorithm has competitive quality. For some examples from the j120 test series the best known solutions were improved and for j60 (50 000 and 500 000 iterations) and for j120 (500 000 iterations) we have obtain the best average deviations of the solutions from the critical path value.

AB - We consider the resource-constrained project scheduling problem with respect to the makespan minimization criterion. The problem accounts for technological constraints of activities precedence together with resource constraints. We propose a genetic algorithm with two versions of crossovers based on the idea of most rational use of constrained resources. The crossovers uses a heuristic that takes into account the degree of criticality for the resources, which is derived from the solution of a relaxed problem with a constraint on accumulative resources. A numerical experiment with examples from the PCPLIB library has shown that the proposed algorithm has competitive quality. For some examples from the j120 test series the best known solutions were improved and for j60 (50 000 and 500 000 iterations) and for j120 (500 000 iterations) we have obtain the best average deviations of the solutions from the critical path value.

KW - genetic algorithms

KW - PCPLIB

KW - renewable resources

KW - resource-constrained project scheduling problem

UR - http://www.scopus.com/inward/record.url?scp=85020666459&partnerID=8YFLogxK

U2 - 10.1134/S0005117917060108

DO - 10.1134/S0005117917060108

M3 - Article

AN - SCOPUS:85020666459

VL - 78

SP - 1101

EP - 1114

JO - Automation and Remote Control

JF - Automation and Remote Control

SN - 0005-1179

IS - 6

ER -

ID: 10184932