A harmony search algorithm for nurse rostering problems

Tools

Hadwan, Mohammed, Ayob, Masri, Kendall, Graham and Qu, Rong (2013) A harmony search algorithm for nurse rostering problems. Information Sciences, 233 . pp. 126-140. ISSN 0020-0255

Full text not available from this repository.

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.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/714689
Additional Information: This is the author’s version of a work that was accepted for publication in Information Sciences. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Information Sciences, 233 (2013) doi: 10.1016/j.ins.2012.12.025.
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number: 10.1016/j.ins.2012.12.025
Depositing User: Qu, Rong
Date Deposited: 15 Mar 2015 22:49
Last Modified: 04 May 2020 16:36
URI: https://eprints.nottingham.ac.uk/id/eprint/28285

Actions (Archive Staff Only)

Edit View Edit View