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A near Pareto optimal approach to student supervisor allocation with two sided preferences and workload balance

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A near Pareto optimal approach to student supervisor allocation with two sided preferences and workload balance

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Sanchez-Anguix, V.; Chalumuri, R.; Aydogan, R.; Julian Inglada, VJ. (2019). A near Pareto optimal approach to student supervisor allocation with two sided preferences and workload balance. Applied Soft Computing. 76:1-15. https://doi.org/10.1016/j.asoc.2018.11.049

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/147518

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Title: A near Pareto optimal approach to student supervisor allocation with two sided preferences and workload balance
Author: Sanchez-Anguix, Víctor Chalumuri, Rithin Aydogan, Reyhan Julian Inglada, Vicente Javier
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat
Issued date:
Embargo end date: 2021-03-31
Abstract:
[EN] The problem of allocating students to supervisors for the development of a personal project or a dissertation is a crucial activity in the higher education environment, as it enables students to get feedback on their ...[+]
Subjects: Genetic algorithms , Student-project allocation , Matching , Pareto optimal , Artificial intelligence
Copyrigths: Embargado
Source:
Applied Soft Computing. (issn: 1568-4946 )
DOI: 10.1016/j.asoc.2018.11.049
Publisher:
Elsevier
Publisher version: https://doi.org/10.1016/j.asoc.2018.11.049
Thanks:
This work is partially supported by funds of the Faculty of Engineering and Computing at Coventry University, United Kingdom, and funds from EU ICT-20-2015 Project SlideWiki granted by the European Commission.
Type: Artículo

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