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Iterative optimization techniques using man–machine interaction for university timetabling problems

We focus on a timetabling problem of university makeup classes and construct a scheduling system based on man–machine interaction which enables to reveal the essential and additional information of the problem domain. In this problem, makeup classes which are requested by the lecturers have to be sc...

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Detalles Bibliográficos
Autores principales: Shimazaki, Syunsuke, Sakakibara, Kazutoshi, Matsumoto, Takuya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4467828/
https://www.ncbi.nlm.nih.gov/pubmed/26090301
http://dx.doi.org/10.1186/s40064-015-1018-3
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author Shimazaki, Syunsuke
Sakakibara, Kazutoshi
Matsumoto, Takuya
author_facet Shimazaki, Syunsuke
Sakakibara, Kazutoshi
Matsumoto, Takuya
author_sort Shimazaki, Syunsuke
collection PubMed
description We focus on a timetabling problem of university makeup classes and construct a scheduling system based on man–machine interaction which enables to reveal the essential and additional information of the problem domain. In this problem, makeup classes which are requested by the lecturers have to be scheduled to a specified time slot under the hard/soft constraints, e.g., schedules of the lecturers and the students. A constraint based scheduling model is newly introduced and several parameters of the model are settled through the repetition of the solution evaluation by the operators. Through the numerical experiment with the actual data, the potential of the proposed approach is examined.
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spelling pubmed-44678282015-06-18 Iterative optimization techniques using man–machine interaction for university timetabling problems Shimazaki, Syunsuke Sakakibara, Kazutoshi Matsumoto, Takuya Springerplus Research We focus on a timetabling problem of university makeup classes and construct a scheduling system based on man–machine interaction which enables to reveal the essential and additional information of the problem domain. In this problem, makeup classes which are requested by the lecturers have to be scheduled to a specified time slot under the hard/soft constraints, e.g., schedules of the lecturers and the students. A constraint based scheduling model is newly introduced and several parameters of the model are settled through the repetition of the solution evaluation by the operators. Through the numerical experiment with the actual data, the potential of the proposed approach is examined. Springer International Publishing 2015-06-12 /pmc/articles/PMC4467828/ /pubmed/26090301 http://dx.doi.org/10.1186/s40064-015-1018-3 Text en © Shimazaki et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Shimazaki, Syunsuke
Sakakibara, Kazutoshi
Matsumoto, Takuya
Iterative optimization techniques using man–machine interaction for university timetabling problems
title Iterative optimization techniques using man–machine interaction for university timetabling problems
title_full Iterative optimization techniques using man–machine interaction for university timetabling problems
title_fullStr Iterative optimization techniques using man–machine interaction for university timetabling problems
title_full_unstemmed Iterative optimization techniques using man–machine interaction for university timetabling problems
title_short Iterative optimization techniques using man–machine interaction for university timetabling problems
title_sort iterative optimization techniques using man–machine interaction for university timetabling problems
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4467828/
https://www.ncbi.nlm.nih.gov/pubmed/26090301
http://dx.doi.org/10.1186/s40064-015-1018-3
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