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Genetic algorithm for the resource-constrained project scheduling problem Full article

Journal Automation and Remote Control
ISSN: 0005-1179 , E-ISSN: 1608-3032
Output data Year: 2017, Volume: 78, Number: 6, Pages: 1101-1114 Pages count : 14 DOI: 10.1134/s0005117917060108
Tags resource-constrained project scheduling problem, renewable resources, genetic algo- rithms, PCPLIB.
Authors Goncharov E.N. 1,2 , Leonov V.V. 2
Affiliations
1 Sobolev Institute of Mathematics
2 Novosibirsk State University

Abstract: Перевод статьи Е.Н. Гончаров, В.В. Леонов Генетический алгоритм для задачи календарного планирования с ограниченными ресурсами // Автоматика и телемеханика, 2017, No 6, c.173–189. 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 (50000 and 500000 iterations) and for j120 (500000 iterations) we have obtain the best average deviations of the solutions from the critical path value.
Cite: Goncharov E.N. , Leonov V.V.
Genetic algorithm for the resource-constrained project scheduling problem
Automation and Remote Control. 2017. V.78. N6. P.1101-1114. DOI: 10.1134/s0005117917060108 WOS Scopus OpenAlex
Original: Гончаров Е.Н. , Леонов В.В.
ГЕНЕТИЧЕСКИЙ АЛГОРИТМ ДЛЯ ЗАДАЧИ КАЛЕНДАРНОГО ПЛАНИРОВАНИЯ С ОГРАНИЧЕННЫМИ РЕСУРСАМИ
Автоматика и телемеханика. 2017. №6. С.173–189.
Dates:
Submitted: Dec 28, 2015
Published print: Jun 1, 2017
Identifiers:
Web of science: WOS:000403538800010
Scopus: 2-s2.0-85020666459
OpenAlex: W2623314515
Citing:
DB Citing
Scopus 33
OpenAlex 41
Web of science 19
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