A centralized solution to the student-school assignment problem in segregated environments via a CUDA parallelized simulated annealing algorithm

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datacite.creatorLincolao-Venegas, Ignacio
datacite.creatorRojas-Mora, Julio
datacite.date2020-11-16
datacite.rightsAcceso Restringido
datacite.subject.englishCUDA
datacite.subject.englishoptimization
datacite.subject.englishparallel computing
datacite.subject.englishsegregation
datacite.titleA centralized solution to the student-school assignment problem in segregated environments via a CUDA parallelized simulated annealing algorithm
dc.date.accessioned2025-06-11T20:24:33Z
dc.date.available2025-06-11T20:24:33Z
dc.descriptionEste trabajo se encuentra enmarcado en el proyecto CONICYT FONDECYT N°11170583. El equipamiento ha sido parcialmente financiado con el proyecto HPC-Cluster UCT: Una iniciativa Interfacultades para el fortalecimiento de la investigacion, vinculación con el medio, y creación de redes de forma interdisciplinaria (VIP FEQUIP2019-INRN-03). © 2020 IEEE. Todos los derechos reservados. El contenido está protegido por derechos de autor y su uso está sujeto a las políticas de IEEE.
dc.description.abstractenIn this work, we implemented a CUDA parallelized simulated annealing algorithm to solve the student-school assignment problem in a highly segregated environment the objective function optimized considered the average distance from the students to their assigned school, the socio-economic segregation via the dissimilarity index, and the cost of schools partially filled. Using data from the MINEDUC, the INE, and the Municipality of Temuco (Chile), we simulated the distribution of Temuco's student population, solving its students' assignment to the city's schools (29853 students to 85 schools) the results obtained were better with a high number of block (simultaneous students exploring), and a low number of threads (simultaneous schools explored by these students) instantiated in the GPU algorithm execution time worsens with the number of blocks and the number of threads, although it remained below 1000 seconds in the worst and below 400 seconds in the best case. However, the algorithm achieves excellent results in reducing socio-economic segregation, taking it from a high level to almost making it disappear. We achieved this result, even with a reduction of the average distance from students to their assigned school.
dc.identifier.doi10.1109/SCCC51225.2020.9281242
dc.identifier.urihttps://repositoriodigital.uct.cl/handle/10925/6402
dc.language.isoes
dc.sourceProceedings - International Conference of the Chilean Computer Science Society
oaire.citationConferenceDate2020-11-16
oaire.citationConferencePlaceCoquimbo, Chile
oaire.citationTitleActas de Congreso
oaire.resourceTypeActas de Congreso
uct.catalogadormlj
uct.departamentoDepartamento de Ingenieria Informatica
uct.indizacionSCOPUS
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