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Genetic-Memetic Relational Approach for Scheduling Problems

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dc.contributor.authorNelyubin, A. P.
dc.contributor.authorMisyurin, S. Y.
dc.contributor.authorМисюрин, Сергей Юрьевич
dc.date.accessioned2024-12-26T10:42:13Z
dc.date.available2024-12-26T10:42:13Z
dc.date.issued2022
dc.description.abstract© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.A general approach to the construction and optimization of schedules is proposed, based on the representation of schedules in the form of a set of binary relations. The description of the schedule in the language of relations is natural and reflects its essential characteristics. It allows us to formalize a lot of flexible constraints involving different priorities, requests, wishes of the schedule participants. It also brings us closer to solving the problem of schedule recognition arising in the process of regular rescheduling. To optimize the schedules, we use a hybrid algorithm scheme that includes genetic, memetic, greedy algorithms, and heuristic rules. The proposed relations are used to encode key scheduling features within the genetic and memetic routine. The relational approach allows us to derive new information maintaining the consistency. As an example of the application of the approach, the formulation of the problem of distribution of objects among a group of autonomous mobile robots during emergency rescue or exploration work is proposed.
dc.format.extentС. 281-287
dc.identifier.citationNelyubin, A. P. Genetic-Memetic Relational Approach for Scheduling Problems / Nelyubin, A.P., Misyurin, S.Y. // Studies in Computational Intelligence. - 2022. - 1032 SCI. - P. 281-287. - 10.1007/978-3-030-96993-6_30
dc.identifier.doi10.1007/978-3-030-96993-6_30
dc.identifier.urihttps://www.doi.org/10.1007/978-3-030-96993-6_30
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dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/28950
dc.relation.ispartofStudies in Computational Intelligence
dc.titleGenetic-Memetic Relational Approach for Scheduling Problems
dc.typeConference Paper
dspace.entity.typePublication
oaire.citation.volume1032 SCI
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