Hybrid and cooperative strategies using harmony search and artificial immune systems for solving the nurse rostering problem

Suk Ho Jin, Ho Yeong Yun, Suk Jae Jeong, Kyung Sup Kim

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

The nurse rostering problem is an important search problem that features many constraints. In a nurse rostering problem, these constraints are defined by processes such as maintaining work regulations, assigning nurse shifts, and considering nurse preferences. A number of approaches to address these constraints, such as penalty function methods, have been investigated in the literature. We propose two types of hybrid metaheuristic approaches for solving the nurse rostering problem, which are based on combining harmony search techniques and artificial immune systems to balance local and global searches and prevent slow convergence speeds and prematurity. The proposed algorithms are evaluated against a benchmarking dataset of nurse rostering problems; the results show that they identify better or best known solutions compared to those identified in other studies for most instances. The results also show that the combination of harmony search and artificial immune systems is better suited than using single metaheuristic or other hybridization methods for finding upper-bound solutions for nurse rostering problems and discrete optimization problems.

Original languageEnglish
Article number1090
JournalSustainability (Switzerland)
Volume9
Issue number7
DOIs
Publication statusPublished - 2017 Jun 22

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Management, Monitoring, Policy and Law

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