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Simheuristics: an introductory tutorial
dc.creator | Juan, Ángel A. | es_ES |
dc.creator | Li, Yuda | es_ES |
dc.creator | Ammouriova, Majsa | es_ES |
dc.creator | Panadero, Javier | es_ES |
dc.creator | Faulín Fajardo, Javier | es_ES |
dc.date.accessioned | 2023-05-16T07:38:57Z | |
dc.date.available | 2023-05-16T07:38:57Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Juan, A. A., Li, Y., Ammouriova, M., Panadero, J., & Faulin, J. (2022). Simheuristics: An introductory tutorial. 2022 Winter Simulation Conference (WSC), 1325-1339. https://doi.org/10.1109/WSC57314.2022.10015318 | en |
dc.identifier.isbn | 978-1-6654-7661-4 | |
dc.identifier.uri | https://hdl.handle.net/2454/45269 | |
dc.description.abstract | Both manufacturing and service industries are subject to uncertainty. Probability techniques and simulation methods allow us to model and analyze complex systems in which stochastic uncertainty is present. When the goal is to optimize the performance of these stochastic systems, simulation by itself is not enough and it needs to be hybridized with optimization methods. Since many real-life optimization problems in the aforementioned industries are NP-hard and large scale, metaheuristic optimization algorithms are required. The simheuristics concept refers to the hybridization of simulation methods and metaheuristic algorithms. This paper provides an introductory tutorial to the concept of simheuristics, showing how it has been successfully employed in solving stochastic optimization problems in many application fields, from production logistics and transportation to telecommunication and insurance. Current research trends in the area of simheuristics, such as their combination with fuzzy logic techniques and machine learning methods, are also discussed. | en |
dc.description.sponsorship | This work has been partially funded by the Spanish Ministry of Science (PID2019-111100RB-C21-C22 /AEI/ 10.13039/501100011033 and RED2018-102642-T), as well as by the Barcelona City Council and Fundació “la Caixa” under the framework of the Barcelona Science Plan 2020–2023 (grant 21S09355-001). Moreover, we appreciate the financial support of the Erasmus+ Program (2019-I-ES01-KA103-062602). | en |
dc.format.mimetype | application/pdf | en |
dc.language.iso | eng | en |
dc.publisher | IEEE | en |
dc.relation.ispartof | 2022 Winter Simulation Conference (WSC): IEEE; 2022. p.1325-1339 978-1-6654-7661-4 | en |
dc.rights | © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en |
dc.subject | Uncertainty | en |
dc.subject | Metaheuristics | en |
dc.subject | Stochastic processes | en |
dc.subject | Transportation | en |
dc.subject | Tutorials | en |
dc.subject | Machine learning | en |
dc.subject | Manufacturing | ene |
dc.title | Simheuristics: an introductory tutorial | en |
dc.type | Contribución a congreso / Biltzarrerako ekarpena | es |
dc.type | info:eu-repo/semantics/conferenceObject | en |
dc.date.updated | 2023-05-16T07:30:46Z | |
dc.contributor.department | Estadística, Informática y Matemáticas | es_ES |
dc.contributor.department | Estatistika, Informatika eta Matematika | eu |
dc.contributor.department | Institute of Smart Cities - ISC | en |
dc.rights.accessRights | Acceso abierto / Sarbide irekia | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | en |
dc.identifier.doi | 10.1109/WSC57314.2022.10015318 | |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-111100RB-C21/ES/ | en |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-111100RB-C22/ES/ | en |
dc.relation.publisherversion | https://doi.org/10.1109/WSC57314.2022.10015318 | |
dc.type.version | Versión aceptada / Onetsi den bertsioa | es |
dc.type.version | info:eu-repo/semantics/acceptedVersion | en |