A harmony search algorithm for nurse rostering problems

Mohammed Hadwan, Masri Ayob, Nasser R. Sabar, Roug Qu

Research output: Contribution to journalArticle

57 Citations (Scopus)

Abstract

Harmony search algorithm (HSA) is a relatively new nature-inspired algorithm. It evolves solutions in the problem search space by mimicking the musical improvisation process in seeking agreeable harmony measured by aesthetic standards. The nurse rostering problem (NRP) is a well-known NP-hard scheduling problem that aims at allocating the required workload to the available staff nurses at healthcare organizations to meet the operational requirements and a range of preferences. This work investigates research issues of the parameter settings in HSA and application of HSA to effectively solve complex NRPs. Due to the well-known fact that most NRPs algorithms are highly problem (or even instance) dependent, the performance of our proposed HSA is evaluated on two sets of very different nurse rostering problems. The first set represents a real world dataset obtained from a large hospital in Malaysia. Experimental results show that our proposed HSA produces better quality rosters for all considered instances than a genetic algorithm (implemented herein). The second is a set of well-known benchmark NRPs which are widely used by researchers in the literature. The proposed HSA obtains good results (and new lower bound for a few instances) when compared to the current state of the art of meta-heuristic algorithms in recent literature.

Original languageEnglish
Pages (from-to)126-140
Number of pages15
JournalInformation Sciences
Volume233
DOIs
Publication statusPublished - 1 Jun 2013

Fingerprint

Harmony Search
Search Algorithm
Malaysia
NP-hard Problems
Metaheuristics
Heuristic algorithm
Healthcare
Search Space
Workload
Nurses
Harmony
Scheduling Problem
Heuristic algorithms
Genetic Algorithm
Benchmark
Lower bound
Dependent
Genetic algorithms
Scheduling
Requirements

Keywords

  • Harmony search
  • Meta-heuristic
  • Timetabling and personnel scheduling

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications
  • Information Systems and Management

Cite this

A harmony search algorithm for nurse rostering problems. / Hadwan, Mohammed; Ayob, Masri; Sabar, Nasser R.; Qu, Roug.

In: Information Sciences, Vol. 233, 01.06.2013, p. 126-140.

Research output: Contribution to journalArticle

Hadwan, Mohammed ; Ayob, Masri ; Sabar, Nasser R. ; Qu, Roug. / A harmony search algorithm for nurse rostering problems. In: Information Sciences. 2013 ; Vol. 233. pp. 126-140.
@article{b7d9d08c14ba49a58661d814aefdd809,
title = "A harmony search algorithm for nurse rostering problems",
abstract = "Harmony search algorithm (HSA) is a relatively new nature-inspired algorithm. It evolves solutions in the problem search space by mimicking the musical improvisation process in seeking agreeable harmony measured by aesthetic standards. The nurse rostering problem (NRP) is a well-known NP-hard scheduling problem that aims at allocating the required workload to the available staff nurses at healthcare organizations to meet the operational requirements and a range of preferences. This work investigates research issues of the parameter settings in HSA and application of HSA to effectively solve complex NRPs. Due to the well-known fact that most NRPs algorithms are highly problem (or even instance) dependent, the performance of our proposed HSA is evaluated on two sets of very different nurse rostering problems. The first set represents a real world dataset obtained from a large hospital in Malaysia. Experimental results show that our proposed HSA produces better quality rosters for all considered instances than a genetic algorithm (implemented herein). The second is a set of well-known benchmark NRPs which are widely used by researchers in the literature. The proposed HSA obtains good results (and new lower bound for a few instances) when compared to the current state of the art of meta-heuristic algorithms in recent literature.",
keywords = "Harmony search, Meta-heuristic, Timetabling and personnel scheduling",
author = "Mohammed Hadwan and Masri Ayob and Sabar, {Nasser R.} and Roug Qu",
year = "2013",
month = "6",
day = "1",
doi = "10.1016/j.ins.2012.12.025",
language = "English",
volume = "233",
pages = "126--140",
journal = "Information Sciences",
issn = "0020-0255",
publisher = "Elsevier Inc.",

}

TY - JOUR

T1 - A harmony search algorithm for nurse rostering problems

AU - Hadwan, Mohammed

AU - Ayob, Masri

AU - Sabar, Nasser R.

AU - Qu, Roug

PY - 2013/6/1

Y1 - 2013/6/1

N2 - Harmony search algorithm (HSA) is a relatively new nature-inspired algorithm. It evolves solutions in the problem search space by mimicking the musical improvisation process in seeking agreeable harmony measured by aesthetic standards. The nurse rostering problem (NRP) is a well-known NP-hard scheduling problem that aims at allocating the required workload to the available staff nurses at healthcare organizations to meet the operational requirements and a range of preferences. This work investigates research issues of the parameter settings in HSA and application of HSA to effectively solve complex NRPs. Due to the well-known fact that most NRPs algorithms are highly problem (or even instance) dependent, the performance of our proposed HSA is evaluated on two sets of very different nurse rostering problems. The first set represents a real world dataset obtained from a large hospital in Malaysia. Experimental results show that our proposed HSA produces better quality rosters for all considered instances than a genetic algorithm (implemented herein). The second is a set of well-known benchmark NRPs which are widely used by researchers in the literature. The proposed HSA obtains good results (and new lower bound for a few instances) when compared to the current state of the art of meta-heuristic algorithms in recent literature.

AB - Harmony search algorithm (HSA) is a relatively new nature-inspired algorithm. It evolves solutions in the problem search space by mimicking the musical improvisation process in seeking agreeable harmony measured by aesthetic standards. The nurse rostering problem (NRP) is a well-known NP-hard scheduling problem that aims at allocating the required workload to the available staff nurses at healthcare organizations to meet the operational requirements and a range of preferences. This work investigates research issues of the parameter settings in HSA and application of HSA to effectively solve complex NRPs. Due to the well-known fact that most NRPs algorithms are highly problem (or even instance) dependent, the performance of our proposed HSA is evaluated on two sets of very different nurse rostering problems. The first set represents a real world dataset obtained from a large hospital in Malaysia. Experimental results show that our proposed HSA produces better quality rosters for all considered instances than a genetic algorithm (implemented herein). The second is a set of well-known benchmark NRPs which are widely used by researchers in the literature. The proposed HSA obtains good results (and new lower bound for a few instances) when compared to the current state of the art of meta-heuristic algorithms in recent literature.

KW - Harmony search

KW - Meta-heuristic

KW - Timetabling and personnel scheduling

UR - http://www.scopus.com/inward/record.url?scp=84875231904&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84875231904&partnerID=8YFLogxK

U2 - 10.1016/j.ins.2012.12.025

DO - 10.1016/j.ins.2012.12.025

M3 - Article

AN - SCOPUS:84875231904

VL - 233

SP - 126

EP - 140

JO - Information Sciences

JF - Information Sciences

SN - 0020-0255

ER -