Optimizing Student Assignment to Educational Establishments: A Many-Objective Approach

This research addresses the problem of Student Allocation to Educational Establishments (SAEE) in a many-objetive optimization context. This problem affects the logistics of educational systems, as it is influenced by parameters such as availability, distance, infrastructure, among others. A first m...

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Autores principales: Casco, María Cecilia, López Pires, Fabio, Barán, Benjamín, Martínez, Eustaquio A.
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2024
Materias:
Ciencias Informáticas
student allocation
many-objective optimization
evolutionary computation
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/176331
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SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-176331
record_format dspace
spelling I19-R120-10915-1763312025-02-10T20:05:01Z http://sedici.unlp.edu.ar/handle/10915/176331 Optimizing Student Assignment to Educational Establishments: A Many-Objective Approach Casco, María Cecilia López Pires, Fabio Barán, Benjamín Martínez, Eustaquio A. 2024-10 2024 2025-02-10T18:03:59Z en Ciencias Informáticas student allocation many-objective optimization evolutionary computation This research addresses the problem of Student Allocation to Educational Establishments (SAEE) in a many-objetive optimization context. This problem affects the logistics of educational systems, as it is influenced by parameters such as availability, distance, infrastructure, among others. A first mathematical formulation of the SAEE problem is proposed with five objective functions for the optimization of: (1) the difference between the number of students assigned and the optimal number of students per class, (2) the average distance between the student’s home and the institution, (3) the use of institutions with better infrastructure, (4) the maximum distance, and (5) the variance of the number of students assigned per class. To solve the proposed formulation, a Multi-Objective Evolutionary Algorithm (MOEA) based on NSGA-II is proposed. To validate this proposal, data provided by the Ministry of Education and Science of Paraguay (MEC) corresponding to Ciudad del Este - Alto Paran´a, from first grade to third grade, of 90 schools and 15,763 students were considered. Experimental results show significant improvements in the variance of the number of students assigned per class (by 22 %), which implies a more balanced distribution of the student population in the classrooms. Red de Universidades con Carreras en Informática Objeto de conferencia Objeto de conferencia http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf 390-400
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
student allocation
many-objective optimization
evolutionary computation
spellingShingle Ciencias Informáticas
student allocation
many-objective optimization
evolutionary computation
Casco, María Cecilia
López Pires, Fabio
Barán, Benjamín
Martínez, Eustaquio A.
Optimizing Student Assignment to Educational Establishments: A Many-Objective Approach
topic_facet Ciencias Informáticas
student allocation
many-objective optimization
evolutionary computation
description This research addresses the problem of Student Allocation to Educational Establishments (SAEE) in a many-objetive optimization context. This problem affects the logistics of educational systems, as it is influenced by parameters such as availability, distance, infrastructure, among others. A first mathematical formulation of the SAEE problem is proposed with five objective functions for the optimization of: (1) the difference between the number of students assigned and the optimal number of students per class, (2) the average distance between the student’s home and the institution, (3) the use of institutions with better infrastructure, (4) the maximum distance, and (5) the variance of the number of students assigned per class. To solve the proposed formulation, a Multi-Objective Evolutionary Algorithm (MOEA) based on NSGA-II is proposed. To validate this proposal, data provided by the Ministry of Education and Science of Paraguay (MEC) corresponding to Ciudad del Este - Alto Paran´a, from first grade to third grade, of 90 schools and 15,763 students were considered. Experimental results show significant improvements in the variance of the number of students assigned per class (by 22 %), which implies a more balanced distribution of the student population in the classrooms.
format Objeto de conferencia
Objeto de conferencia
author Casco, María Cecilia
López Pires, Fabio
Barán, Benjamín
Martínez, Eustaquio A.
author_facet Casco, María Cecilia
López Pires, Fabio
Barán, Benjamín
Martínez, Eustaquio A.
author_sort Casco, María Cecilia
title Optimizing Student Assignment to Educational Establishments: A Many-Objective Approach
title_short Optimizing Student Assignment to Educational Establishments: A Many-Objective Approach
title_full Optimizing Student Assignment to Educational Establishments: A Many-Objective Approach
title_fullStr Optimizing Student Assignment to Educational Establishments: A Many-Objective Approach
title_full_unstemmed Optimizing Student Assignment to Educational Establishments: A Many-Objective Approach
title_sort optimizing student assignment to educational establishments: a many-objective approach
publishDate 2024
url http://sedici.unlp.edu.ar/handle/10915/176331
work_keys_str_mv AT cascomariacecilia optimizingstudentassignmenttoeducationalestablishmentsamanyobjectiveapproach
AT lopezpiresfabio optimizingstudentassignmenttoeducationalestablishmentsamanyobjectiveapproach
AT baranbenjamin optimizingstudentassignmenttoeducationalestablishmentsamanyobjectiveapproach
AT martinezeustaquioa optimizingstudentassignmenttoeducationalestablishmentsamanyobjectiveapproach
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