Bee Colony Algorithm for Proctors Assignment.

Proctor assignment refers to assigning proctors to examinations with the objective of having the appropriate number of proctors assigned to examinations, subject to conditions such as minimizing the load of proctoring and preventing any conflicting assignments. This problem is intractable, and hence...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي: Mansour, Nashat (author)
مؤلفون آخرون: Taha, Mohamad Kassem (author)
التنسيق: article
منشور في: 2015
الوصول للمادة أونلاين:http://hdl.handle.net/10725/7833
http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php
http://203.83.208.81/index.php/itii/article/view/46
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author Mansour, Nashat
author2 Taha, Mohamad Kassem
author2_role author
author_facet Mansour, Nashat
Taha, Mohamad Kassem
author_role author
dc.creator.none.fl_str_mv Mansour, Nashat
Taha, Mohamad Kassem
dc.date.none.fl_str_mv 2015
2018-05-16T10:47:50Z
2018-05-16T10:47:50Z
2018-05-16
dc.identifier.none.fl_str_mv http://hdl.handle.net/10725/7833
Mansour, N., & Taha, M. K. (2015). Bee Colony Algorithm for Proctors Assignment. INFORMATION TECHNOLOGY IN INDUSTRY, 3(2), 59-63.
http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php
http://203.83.208.81/index.php/itii/article/view/46
dc.language.none.fl_str_mv en
dc.relation.none.fl_str_mv Information technology in industy
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.title.none.fl_str_mv Bee Colony Algorithm for Proctors Assignment.
dc.type.none.fl_str_mv Article
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description Proctor assignment refers to assigning proctors to examinations with the objective of having the appropriate number of proctors assigned to examinations, subject to conditions such as minimizing the load of proctoring and preventing any conflicting assignments. This problem is intractable, and hence, heuristics algorithms are needed to find good solutions. In this paper, we propose a new solution for the proctor assignment problem based on the Bee Colony meta-heuristic algorithm. The Bee Colony algorithm is a recent population-based search algorithm that mimics the natural behavior of swarms of honey bees during the process of collecting food. The algorithm performs a neighborhood search combined with a random search to balance exploration and exploitation. The food source identified by a honey bee is associated with a candidate solution to the proctors assignment problem. The search accomplished by three types of bees over a number of iterations aiming to find the source with the highest nectar value (fitness value of a candidate solution). We apply the Bee Colony algorithm to previously published data. Experimental results show good solutions that maximize the preferences of proctors while preserving the fairness of the workload given to proctors. The results also show that the Bee Colony algorithm outperforms other methods on most subject problems.
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identifier_str_mv Mansour, N., & Taha, M. K. (2015). Bee Colony Algorithm for Proctors Assignment. INFORMATION TECHNOLOGY IN INDUSTRY, 3(2), 59-63.
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spelling Bee Colony Algorithm for Proctors Assignment.Mansour, NashatTaha, Mohamad KassemProctor assignment refers to assigning proctors to examinations with the objective of having the appropriate number of proctors assigned to examinations, subject to conditions such as minimizing the load of proctoring and preventing any conflicting assignments. This problem is intractable, and hence, heuristics algorithms are needed to find good solutions. In this paper, we propose a new solution for the proctor assignment problem based on the Bee Colony meta-heuristic algorithm. The Bee Colony algorithm is a recent population-based search algorithm that mimics the natural behavior of swarms of honey bees during the process of collecting food. The algorithm performs a neighborhood search combined with a random search to balance exploration and exploitation. The food source identified by a honey bee is associated with a candidate solution to the proctors assignment problem. The search accomplished by three types of bees over a number of iterations aiming to find the source with the highest nectar value (fitness value of a candidate solution). We apply the Bee Colony algorithm to previously published data. Experimental results show good solutions that maximize the preferences of proctors while preserving the fairness of the workload given to proctors. The results also show that the Bee Colony algorithm outperforms other methods on most subject problems.PublishedN/A2018-05-16T10:47:50Z2018-05-16T10:47:50Z20152018-05-16Articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10725/7833Mansour, N., & Taha, M. K. (2015). Bee Colony Algorithm for Proctors Assignment. INFORMATION TECHNOLOGY IN INDUSTRY, 3(2), 59-63.http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.phphttp://203.83.208.81/index.php/itii/article/view/46enInformation technology in industyinfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/78332021-03-19T10:43:16Z
spellingShingle Bee Colony Algorithm for Proctors Assignment.
Mansour, Nashat
status_str publishedVersion
title Bee Colony Algorithm for Proctors Assignment.
title_full Bee Colony Algorithm for Proctors Assignment.
title_fullStr Bee Colony Algorithm for Proctors Assignment.
title_full_unstemmed Bee Colony Algorithm for Proctors Assignment.
title_short Bee Colony Algorithm for Proctors Assignment.
title_sort Bee Colony Algorithm for Proctors Assignment.
url http://hdl.handle.net/10725/7833
http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php
http://203.83.208.81/index.php/itii/article/view/46