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BASA: An improved hybrid bees algorithm for the single machine scheduling with early/tardy jobs

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BASA: An improved hybrid bees algorithm for the single machine scheduling with early/tardy jobs

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dc.contributor.author Abdessemed, Ahmed Adnane es_ES
dc.contributor.author Mouss, Leila Hayet es_ES
dc.contributor.author Benaggoune, Khaled es_ES
dc.date.accessioned 2023-11-07T10:07:26Z
dc.date.available 2023-11-07T10:07:26Z
dc.date.issued 2023-07-31
dc.identifier.uri http://hdl.handle.net/10251/199415
dc.description.abstract [EN] In this paper, we present a novel hybrid meta-heuristic by enhancing the Basic Bees Algorithm through the integration of a local search method namely Simulated Annealing and Variable Neighbourhood Search like algorithm. The resulted hybrid bees algorithm (BASA) is used to solve the Single Machine Scheduling Problem with Early/Tardy jobs, where the generated outcomes are compared against the Basic Bees Algorithm (BA), and against some stat-of-the-art meta-heuristics. Computational results reveal that our proposed framework outperforms the Basic Bees Algorithm, and demonstrates a competitive performance compared with some algorithms extracted from the literature. es_ES
dc.language Inglés es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.relation.ispartof International Journal of Production Management and Engineering es_ES
dc.rights Reconocimiento - No comercial - Compartir igual (by-nc-sa) es_ES
dc.subject Bees Algorithm es_ES
dc.subject Single Machine Scheduling es_ES
dc.subject Early/Tardy es_ES
dc.subject Simulated Annealing es_ES
dc.subject Meta-heuristic es_ES
dc.title BASA: An improved hybrid bees algorithm for the single machine scheduling with early/tardy jobs es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.4995/ijpme.2023.18077
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Abdessemed, AA.; Mouss, LH.; Benaggoune, K. (2023). BASA: An improved hybrid bees algorithm for the single machine scheduling with early/tardy jobs. International Journal of Production Management and Engineering. 11(2):167-177. https://doi.org/10.4995/ijpme.2023.18077 es_ES
dc.description.accrualMethod OJS es_ES
dc.relation.publisherversion https://doi.org/10.4995/ijpme.2023.18077 es_ES
dc.description.upvformatpinicio 167 es_ES
dc.description.upvformatpfin 177 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 11 es_ES
dc.description.issue 2 es_ES
dc.identifier.eissn 2340-4876
dc.relation.pasarela OJS\18077 es_ES
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