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dc.contributor.authorMéndez-Fernández, Isabel
dc.contributor.authorLorenzo Freire, Silvia
dc.contributor.authorGonzález Rueda, Ángel Manuel
dc.date.accessioned2023-11-16T13:50:55Z
dc.date.available2023-11-16T13:50:55Z
dc.date.issued2023-11
dc.identifier.citationI. Méndez-Fernández, S. Lorenzo-Freire, and Á.M. González-Rueda, "An Adaptive Large Neighbourhood Search algorithm for a real-world Home Care Scheduling Problem with time windows and dynamic breaks", Computers and Operations Research, Vol. 159, November 2023, article 106351, doi: 10.1016/j.cor.2023.106351es_ES
dc.identifier.urihttp://hdl.handle.net/2183/34267
dc.descriptionFinanciado para publicación en acceso aberto: Universidade da Coruña/CISUGes_ES
dc.description.abstract[Abstract]: This paper presents a Home Care Scheduling Problem (from now on HCSP) based on a real case of a care company for elderly and dependent people located in the North of Spain. The problem incorporates many of the common features addressed in the HCSP literature, such as soft and hard time windows for the services, available working time of the caregivers or affinity levels between users and caregivers. However, it also includes other novel characteristics that increase the difficulty of the problem significantly, since the breaks between services will play a key role in the quality of the solutions. To evaluate the solutions, the users welfare will be prioritized over the cost associated with the schedule. The problem has been formulated as a Mixed Integer Linear Programming (MILP) one but, due to the complexity of the model, it is not possible to solve it for real size instances. Therefore, we have designed a method that combines the Adaptive Large Neighbourhood Search (ALNS) methodology with a heuristic approach necessary to evaluate the objective functions. To analyse the behaviour of the algorithm, a set of computational experiments are carried out under different configurations. First, the MILP formulation and the algorithm have been compared over some standard instances from the literature. Finally, the performance of the algorithm is evaluated over a real case study based on the timetables of the company during some weeks from 2016 to 2017.es_ES
dc.description.sponsorshipThis research was funded by MICINN/AEI/10.13039/501100011033/ and ERDF/EU through R+D+I project grants MTM2017-87197-C3-1-P and PID2021-124030NB-C31 and by Consellería de Cultura, Educación e Universidades, Xunta de Galicia (Grupos de Referencia Competitiva ED431C-2020/14 and Centro de Investigación del Sistema universitario de Galicia ED431G-2019/01). Funding for open access charge: Universidade da Coruña/CISUG. Constructive comments from several referees and the editor are also gratefully acknowledged.es_ES
dc.description.sponsorshipXunta de Galicia; ED431C-2020/14es_ES
dc.description.sponsorshipXunta de Galicia; ED431G-2019/01es_ES
dc.language.isoenges_ES
dc.publisherElsevier Ltdes_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2017-87197-C3-1-P/ES/OPTIMIZACION Y COOPERACION CON APLICACIONES EN ECONOMIA, ENERGIA Y LOGISTICAes_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023/PID2021-124030NB-C31/ES/OPTIMIZACIÓN, APRENDIZAJE Y COOPERACIÓN CON APLICACIONES EN LOGÍSTICAes_ES
dc.relation.urihttps://doi.org/10.1016/j.cor.2023.106351es_ES
dc.rightsAtribución 4.0 Internacional (CC BY 4.0)es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectAdaptive large neighbourhood searches_ES
dc.subjectHome carees_ES
dc.subjectMixed integer linear programminges_ES
dc.subjectSchedulinges_ES
dc.titleAn Adaptive Large Neighbourhood Search algorithm for a real-world Home Care Scheduling Problem with time windows and dynamic breakses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleComputers and Operations Researches_ES
UDC.volume159es_ES
UDC.startPage106351es_ES
dc.identifier.doi10.1016/j.cor.2023.106351


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