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A Tabu Search Approach with Embedded Nurse Preferences for Solving Nurse Rostering Problem

This paper presents an intelligent tabu search (TS) approach for solving a complex real-world nurse rostering problem (NRP). Previous study has suggested that improvement on neighborhoods and smart intensification of a TS could produce faster and fitted solution. In order to enhance the TS, this pap...

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Main Authors: Ramli, Razamin, Ahmad, Siti Nurin Ima, Abdul-Rahman, Syariza, Wibowo, Antoni
Format: Article
Language:English
Published: EDP Sciences 2020
Subjects:
QA Mathematics
Online Access:https://repo.uum.edu.my/id/eprint/30991/1/IJSMDO%2011%2010%202020%2001-10.pdf
https://doi.org/10.1051/smdo/2020002
https://repo.uum.edu.my/id/eprint/30991/
https://www.ijsmdo.org/articles/smdo/full_html/2020/01/smdo190028/smdo190028.html
https://doi.org/10.1051/smdo/2020002
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spelling my.uum.repo.309912024-07-04T03:30:50Z https://repo.uum.edu.my/id/eprint/30991/ A Tabu Search Approach with Embedded Nurse Preferences for Solving Nurse Rostering Problem Ramli, Razamin Ahmad, Siti Nurin Ima Abdul-Rahman, Syariza Wibowo, Antoni QA Mathematics This paper presents an intelligent tabu search (TS) approach for solving a complex real-world nurse rostering problem (NRP). Previous study has suggested that improvement on neighborhoods and smart intensification of a TS could produce faster and fitted solution. In order to enhance the TS, this paper introduces an improvement to the neighborhoods and explores on the neighborhoods exploitations of TS to solve the NRP. The methodology consists of two phases: initialization and neighborhood. The semi-random initialization is employed for finding a good initial solution during the initialization phase which avoids the violation of hard constraints, while the neighborhood phase is established for further improving the solution quality with a special representation and innovative neighborhood generations within TS algorithm. The aim is to move sample points towards a high-quality solution while avoiding local optima by utilising a calculated force value. It is observed that the enhancement strategy could improve the solution quality of the constructed roster. It is concluded that the TS with enhancements approach is able to assign effective and efficient shift duties for the NRP especially when related with real-world working regulations and nurses preferences EDP Sciences 2020 Article PeerReviewed application/pdf en cc4_by https://repo.uum.edu.my/id/eprint/30991/1/IJSMDO%2011%2010%202020%2001-10.pdf Ramli, Razamin and Ahmad, Siti Nurin Ima and Abdul-Rahman, Syariza and Wibowo, Antoni (2020) A Tabu Search Approach with Embedded Nurse Preferences for Solving Nurse Rostering Problem. International Journal for Simulation and Multidisciplinary Design Optimization, 11 (10). pp. 1-10. ISSN 1779-6288 https://www.ijsmdo.org/articles/smdo/full_html/2020/01/smdo190028/smdo190028.html https://doi.org/10.1051/smdo/2020002 https://doi.org/10.1051/smdo/2020002
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutional Repository
url_provider http://repo.uum.edu.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Ramli, Razamin
Ahmad, Siti Nurin Ima
Abdul-Rahman, Syariza
Wibowo, Antoni
A Tabu Search Approach with Embedded Nurse Preferences for Solving Nurse Rostering Problem
description This paper presents an intelligent tabu search (TS) approach for solving a complex real-world nurse rostering problem (NRP). Previous study has suggested that improvement on neighborhoods and smart intensification of a TS could produce faster and fitted solution. In order to enhance the TS, this paper introduces an improvement to the neighborhoods and explores on the neighborhoods exploitations of TS to solve the NRP. The methodology consists of two phases: initialization and neighborhood. The semi-random initialization is employed for finding a good initial solution during the initialization phase which avoids the violation of hard constraints, while the neighborhood phase is established for further improving the solution quality with a special representation and innovative neighborhood generations within TS algorithm. The aim is to move sample points towards a high-quality solution while avoiding local optima by utilising a calculated force value. It is observed that the enhancement strategy could improve the solution quality of the constructed roster. It is concluded that the TS with enhancements approach is able to assign effective and efficient shift duties for the NRP especially when related with real-world working regulations and nurses preferences
format Article
author Ramli, Razamin
Ahmad, Siti Nurin Ima
Abdul-Rahman, Syariza
Wibowo, Antoni
author_facet Ramli, Razamin
Ahmad, Siti Nurin Ima
Abdul-Rahman, Syariza
Wibowo, Antoni
author_sort Ramli, Razamin
title A Tabu Search Approach with Embedded Nurse Preferences for Solving Nurse Rostering Problem
title_short A Tabu Search Approach with Embedded Nurse Preferences for Solving Nurse Rostering Problem
title_full A Tabu Search Approach with Embedded Nurse Preferences for Solving Nurse Rostering Problem
title_fullStr A Tabu Search Approach with Embedded Nurse Preferences for Solving Nurse Rostering Problem
title_full_unstemmed A Tabu Search Approach with Embedded Nurse Preferences for Solving Nurse Rostering Problem
title_sort tabu search approach with embedded nurse preferences for solving nurse rostering problem
publisher EDP Sciences
publishDate 2020
url https://repo.uum.edu.my/id/eprint/30991/1/IJSMDO%2011%2010%202020%2001-10.pdf
https://doi.org/10.1051/smdo/2020002
https://repo.uum.edu.my/id/eprint/30991/
https://www.ijsmdo.org/articles/smdo/full_html/2020/01/smdo190028/smdo190028.html
https://doi.org/10.1051/smdo/2020002
_version_ 1804069251557883904
score 13.211869

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