An improved fair nurse scheduling optimisation using particle swarm intelligent technique

Nurse schedule is a list showing the arrangement such as dates and times of each employee must work at a particular period of time. Nurse scheduling is one of the important and complex tasks which influence the hospital productivity. Common issues in nurse scheduling problem are the unfair of the wo...

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Main Author:	Ramli, Mohamad Raziff
Format:	Thesis
Language:	English English
Published:	2015
Subjects:	T Technology (General) TS Manufactures
Online Access:	http://eprints.utem.edu.my/id/eprint/16854/1/An%20Improved%20Fair%20Nurse%20Scheduling%20Optimisation%20Using%20Particle%20Swarm%20Intelligent%20Technique.pdf http://eprints.utem.edu.my/id/eprint/16854/2/An%20improved%20fair%20nurse%20scheduling%20optimisation%20using%20particle%20swarm%20intelligent%20technique.pdf
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id	my-utem-ep.16854
record_format	uketd_dc
institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	English English
advisor	Hussin, Burairah
topic	T Technology (General) TS Manufactures
spellingShingle	T Technology (General) TS Manufactures Ramli, Mohamad Raziff An improved fair nurse scheduling optimisation using particle swarm intelligent technique
description	Nurse schedule is a list showing the arrangement such as dates and times of each employee must work at a particular period of time. Nurse scheduling is one of the important and complex tasks which influence the hospital productivity. Common issues in nurse scheduling problem are the unfair of the working shifts between nurses and the shortages of nursing staffs combined with the uncertain nature of patient workloads. Assigning each available nurse to the right place at the right time is therefore a major concern among many modern hospitals. A well-designed schedule algorithm shall be able to generate an efficient task that can precede the restriction and variability. Nevertheless, the fairness of the task been assigned to the nurses should also considered nurses perspectives. Therefore, this research aims to propose practical and effective nurse scheduling approach that takes into consideration both preferences by hospital and nurse. The suggested approach provides better solution not only with respect to efficiency but also the quality of the nurse scheduling to the hospital and the nurse themselves. Particle Swarm Optimisation (PSO) has many successful applications in continuous optimisation problems, thus, the capability of PSO is used to provide a high performance predictive nurse schedule. The nurse schedule produced by PSO then will investigate and compared with real schedule while the data successfully tested on benchmark and verified base on fairness measures. The experimental results have positively shown that the nurse schedule generated by PSO much better and effective in providing reasonably high quality solutions with respect to the desired hospital.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Ramli, Mohamad Raziff
author_facet	Ramli, Mohamad Raziff
author_sort	Ramli, Mohamad Raziff
title	An improved fair nurse scheduling optimisation using particle swarm intelligent technique
title_short	An improved fair nurse scheduling optimisation using particle swarm intelligent technique
title_full	An improved fair nurse scheduling optimisation using particle swarm intelligent technique
title_fullStr	An improved fair nurse scheduling optimisation using particle swarm intelligent technique
title_full_unstemmed	An improved fair nurse scheduling optimisation using particle swarm intelligent technique
title_sort	improved fair nurse scheduling optimisation using particle swarm intelligent technique
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty of Information and Communication Technology
publishDate	2015
url	http://eprints.utem.edu.my/id/eprint/16854/1/An%20Improved%20Fair%20Nurse%20Scheduling%20Optimisation%20Using%20Particle%20Swarm%20Intelligent%20Technique.pdf http://eprints.utem.edu.my/id/eprint/16854/2/An%20improved%20fair%20nurse%20scheduling%20optimisation%20using%20particle%20swarm%20intelligent%20technique.pdf
_version_	1747833900961366016
spelling	my-utem-ep.168542022-04-20T11:06:23Z An improved fair nurse scheduling optimisation using particle swarm intelligent technique 2015 Ramli, Mohamad Raziff T Technology (General) TS Manufactures Nurse schedule is a list showing the arrangement such as dates and times of each employee must work at a particular period of time. Nurse scheduling is one of the important and complex tasks which influence the hospital productivity. Common issues in nurse scheduling problem are the unfair of the working shifts between nurses and the shortages of nursing staffs combined with the uncertain nature of patient workloads. Assigning each available nurse to the right place at the right time is therefore a major concern among many modern hospitals. A well-designed schedule algorithm shall be able to generate an efficient task that can precede the restriction and variability. Nevertheless, the fairness of the task been assigned to the nurses should also considered nurses perspectives. Therefore, this research aims to propose practical and effective nurse scheduling approach that takes into consideration both preferences by hospital and nurse. The suggested approach provides better solution not only with respect to efficiency but also the quality of the nurse scheduling to the hospital and the nurse themselves. Particle Swarm Optimisation (PSO) has many successful applications in continuous optimisation problems, thus, the capability of PSO is used to provide a high performance predictive nurse schedule. The nurse schedule produced by PSO then will investigate and compared with real schedule while the data successfully tested on benchmark and verified base on fairness measures. The experimental results have positively shown that the nurse schedule generated by PSO much better and effective in providing reasonably high quality solutions with respect to the desired hospital. 2015 Thesis http://eprints.utem.edu.my/id/eprint/16854/ http://eprints.utem.edu.my/id/eprint/16854/1/An%20Improved%20Fair%20Nurse%20Scheduling%20Optimisation%20Using%20Particle%20Swarm%20Intelligent%20Technique.pdf text en public http://eprints.utem.edu.my/id/eprint/16854/2/An%20improved%20fair%20nurse%20scheduling%20optimisation%20using%20particle%20swarm%20intelligent%20technique.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=96168 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Information and Communication Technology Hussin, Burairah 1. Abidi, S.S. and Goh, a, 2000. A personalised Healthcare Information Delivery System: pushing customised healthcare information over the WWW. 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An improved fair nurse scheduling optimisation using particle swarm intelligent technique

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