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Genetic algorithm for the resource-constrained project scheduling problem Научная публикация

Журнал Automation and Remote Control
ISSN: 0005-1179 , E-ISSN: 1608-3032
Вых. Данные Год: 2017, Том: 78, Номер: 6, Страницы: 1101-1114 Страниц : 14 DOI: 10.1134/s0005117917060108
Ключевые слова resource-constrained project scheduling problem, renewable resources, genetic algo- rithms, PCPLIB.
Авторы Goncharov E.N. 1,2 , Leonov V.V. 2
Организации
1 Sobolev Institute of Mathematics
2 Novosibirsk State University

Реферат: 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.
Библиографическая ссылка: 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
Оригинальная: Гончаров Е.Н. , Леонов В.В.
ГЕНЕТИЧЕСКИЙ АЛГОРИТМ ДЛЯ ЗАДАЧИ КАЛЕНДАРНОГО ПЛАНИРОВАНИЯ С ОГРАНИЧЕННЫМИ РЕСУРСАМИ
Автоматика и телемеханика. 2017. №6. С.173–189.
Даты:
Поступила в редакцию: 28 дек. 2015 г.
Опубликована в печати: 1 июн. 2017 г.
Идентификаторы БД:
Web of science: WOS:000403538800010
Scopus: 2-s2.0-85020666459
OpenAlex: W2623314515
Цитирование в БД:
БД Цитирований
Scopus 33
OpenAlex 41
Web of science 19
Альметрики: