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dc.contributor.authorDíaz, Hernán
dc.contributor.authorPalacios, Juan José
dc.contributor.authorGonzález Rodríguez, Inés 
dc.contributor.authorVela, Camino R.
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2023-03-17T14:51:38Z
dc.date.available2023-05-24T00:22:12Z
dc.date.issued2022
dc.identifier.isbn978-3-031-06527-9
dc.identifier.otherPID2019-106263RB-I00
dc.identifier.urihttps://hdl.handle.net/10902/28237
dc.description.abstractThis paper addresses a variant of the Job Shop Scheduling Problem with makespan minimisation where uncertainty in task durations is taken into account and modelled with intervals. Given the problem’s complexity, we tackle it using a metaheuristic approach. Specifically, we propose a novel Artificial Bee Colony algorithm incorporating three different selection mechanisms that help in guiding the search towards more promising areas. A parametric analysis is conducted and a comparison of the different selection strategies is performed on a set of benchmark instances. The results illustrate the benefit of using the new guiding strategies, improving the behaviour of the ABC algorithm, which compares favourably to the state-of-the art in the problem. An additional study is conducted to assess the robustness of the solutions obtained under each guiding strategy.es_ES
dc.description.sponsorshipSupported by the Spanish Government under research grant PID2019-106263RB-I00 and by the Asturias Government under research grant Severo Ochoa.es_ES
dc.format.extent11 p.es_ES
dc.language.isoenges_ES
dc.sourceBio-inspired Systems and Applications: from Robotics to Ambient Intelligence. IWINAC 2022. Lecture Notes in Computer Science, 2022, 13259, 98–108es_ES
dc.subject.otherJob Shop Schedulinges_ES
dc.subject.otherMakespanes_ES
dc.subject.otherInterval Uncertaintyes_ES
dc.subject.otherArtificial Bee Colonyes_ES
dc.titleElite Artificial Bee Colony for Makespan Optimisation in Job Shop with Interval Uncertaintyes_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.relation.publisherVersionhttps://doi.org/10.1007/978-3-031-06527-9_10es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1007/978-3-031-06527-9_10
dc.type.versionacceptedVersiones_ES


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