Abstract: Some scheduling problems taking into account energy consumption are considered. Such problems arise in multiprocessor computer systems and take into account resource constraints and parallelization capabilities. For these problems, some algorithms of greedy and list types with guaranteed accuracy estimates in the worst case are known. In this paper, we propose an adaptive genetic algorithm with decoding solutions based on the specifics of the problem statements. A peculiarity is that the crossover operator solves a problem of optimal recombination in full and truncated versions. The call of the crossover operators is implemented adaptively. The categorical and numerical parameters are adjusted adaptively by using modern packages. The results of an experimental study show a statistically significant advantage over the known algorithms on a series of problems of different structure.

Cite: Sakhno M.Y.
An adaptive genetic algorithm with optimal recombination for scheduling problems with energy resource
Numerical Analysis and Applications. 2025. V.18. N3. P.268-282. DOI: 10.1134/S1995423925030073 WOS Scopus РИНЦ

Original: Сахно М.Ю.
Адаптивный генетический алгоритм с оптимальной рекомбинацией для задачи составления расписаний с учетом расхода энергии
Сибирский журнал вычислительной математики. 2025. Т.28. №3. С.327-346. DOI: 10.15372/SJNM20250307 РИНЦ

Dates:

Submitted:	Jul 30, 2024
Accepted:	Mar 4, 2025
Published print:	Oct 25, 2025
Published online:	Oct 25, 2025

Identifiers:

Web of science:	WOS:001601043200004
Scopus:	2-s2.0-105019696761
Elibrary:	83115192

Citing: Пока нет цитирований

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