Ant colony optimization with semi random initialization for nurse rostering problem

A nurse rostering problem is an NP-Hard problem that is difficult to solve during the complexity of the problem. Since good scheduling is the schedule that fulfilled the hard constraint and minimizes the violation of soft constraint, a lot of approaches is implemented to improve the quality of the s...

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Autores principales:	Achmad Said, Wibowo Antoni, Diana Diana
Formato:	article
Lenguaje:	EN
Publicado:	EDP Sciences 2021
Materias:	scheduling nurse rostering problem ant colony optimization optimization Industrial engineering. Management engineering T55.4-60.8 Industrial directories T11.95-12.5
Acceso en línea:	https://doaj.org/article/1f816243fcf8476c9c8f7aa3f8e0436a
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spelling	oai:doaj.org-article:1f816243fcf8476c9c8f7aa3f8e0436a2021-11-12T11:45:49ZAnt colony optimization with semi random initialization for nurse rostering problem1779-628810.1051/smdo/2021030https://doaj.org/article/1f816243fcf8476c9c8f7aa3f8e0436a2021-01-01T00:00:00Zhttps://www.ijsmdo.org/articles/smdo/full_html/2021/01/smdo210083/smdo210083.htmlhttps://doaj.org/toc/1779-6288A nurse rostering problem is an NP-Hard problem that is difficult to solve during the complexity of the problem. Since good scheduling is the schedule that fulfilled the hard constraint and minimizes the violation of soft constraint, a lot of approaches is implemented to improve the quality of the schedule. This research proposed an improvement on ant colony optimization with semi-random initialization for nurse rostering problems. Semi-random initialization is applied to avoid violation of the hard constraint, and then the violation of soft constraint will be minimized using ant colony optimization. Semi-random initialization will improve the construction solution phase by assigning nurses directly to the shift that is related to the hard constraint, so the violation of hard constraint will be avoided from the beginning part. The scheduling process will complete by pheromone value by giving weight to the rest available shift during the ant colony optimization process. This proposed method is tested using a real-world problem taken from St. General Hospital Elisabeth. The objective function is formulated to minimize the violation of the constraints and balance nurse workload. The performance of the proposed method is examined by using different dimension problems, with the same number of ant and iteration. The proposed method is also compared to conventional ant colony optimization and genetic algorithm for performance comparison. The experiment result shows that the proposed method performs better with small to medium dimension problems. The semi-random initialization is a success to avoid violation of the hard constraint and minimize the objective value by about 24%. The proposed method gets the lowest objective value with 0,76 compared to conventional ant colony optimization with 124 and genetic algorithm with 1.Achmad SaidWibowo AntoniDiana DianaEDP Sciencesarticleschedulingnurse rostering problemant colony optimizationoptimizationIndustrial engineering. Management engineeringT55.4-60.8Industrial directoriesT11.95-12.5ENInternational Journal for Simulation and Multidisciplinary Design Optimization, Vol 12, p 31 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	scheduling nurse rostering problem ant colony optimization optimization Industrial engineering. Management engineering T55.4-60.8 Industrial directories T11.95-12.5
spellingShingle	scheduling nurse rostering problem ant colony optimization optimization Industrial engineering. Management engineering T55.4-60.8 Industrial directories T11.95-12.5 Achmad Said Wibowo Antoni Diana Diana Ant colony optimization with semi random initialization for nurse rostering problem
description	A nurse rostering problem is an NP-Hard problem that is difficult to solve during the complexity of the problem. Since good scheduling is the schedule that fulfilled the hard constraint and minimizes the violation of soft constraint, a lot of approaches is implemented to improve the quality of the schedule. This research proposed an improvement on ant colony optimization with semi-random initialization for nurse rostering problems. Semi-random initialization is applied to avoid violation of the hard constraint, and then the violation of soft constraint will be minimized using ant colony optimization. Semi-random initialization will improve the construction solution phase by assigning nurses directly to the shift that is related to the hard constraint, so the violation of hard constraint will be avoided from the beginning part. The scheduling process will complete by pheromone value by giving weight to the rest available shift during the ant colony optimization process. This proposed method is tested using a real-world problem taken from St. General Hospital Elisabeth. The objective function is formulated to minimize the violation of the constraints and balance nurse workload. The performance of the proposed method is examined by using different dimension problems, with the same number of ant and iteration. The proposed method is also compared to conventional ant colony optimization and genetic algorithm for performance comparison. The experiment result shows that the proposed method performs better with small to medium dimension problems. The semi-random initialization is a success to avoid violation of the hard constraint and minimize the objective value by about 24%. The proposed method gets the lowest objective value with 0,76 compared to conventional ant colony optimization with 124 and genetic algorithm with 1.
format	article
author	Achmad Said Wibowo Antoni Diana Diana
author_facet	Achmad Said Wibowo Antoni Diana Diana
author_sort	Achmad Said
title	Ant colony optimization with semi random initialization for nurse rostering problem
title_short	Ant colony optimization with semi random initialization for nurse rostering problem
title_full	Ant colony optimization with semi random initialization for nurse rostering problem
title_fullStr	Ant colony optimization with semi random initialization for nurse rostering problem
title_full_unstemmed	Ant colony optimization with semi random initialization for nurse rostering problem
title_sort	ant colony optimization with semi random initialization for nurse rostering problem
publisher	EDP Sciences
publishDate	2021
url	https://doaj.org/article/1f816243fcf8476c9c8f7aa3f8e0436a
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Ant colony optimization with semi random initialization for nurse rostering problem

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