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Hybridization of harmony search with hill climbing for highly constrained nurse rostering problem

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Abstract

This paper proposes a hybrid harmony search algorithm (HHSA) for solving the highly constrained nurse rostering problem (NRP). The NRP is a combinatorial optimization problem tackled by assigning a set of shifts to a set of nurses; each has specific skills and work contract, to a predefined rostering period according to a set of constraints. The harmony search is a metaheuristic approach, where the metaheuristics are the most successful methods for tackling this problem. In HHSA, the harmony search algorithm is hybridized with the hill climbing optimizer to empower its exploitation capability. Furthermore, the memory consideration operator of the HHSA is modified by replacing the random selection scheme with the global-best concept of particle swarm optimization to accelerate its convergence rate. The standard dataset published in the first international nurse rostering competition 2010 (INRC2010) was utilized to evaluate the proposed HHSA. Several convergence scenarios have been employed to study the effects of the two HHSA modifications. Finally, a comparative evaluation against twelve other methods that worked on the INRC2010 dataset is carried out. The experimental results show that the proposed method achieved five new best results, and 33 best published results out of 69 instances as achieved by other comparative methods.

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Notes

  1. http://www.cs.nott.ac.uk/tec/NRP/.

  2. https://www.kuleuven-kulak.be/nrpcompetition.

  3. http://mobiz.vives.be/inrc2/.

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Authors and Affiliations

  1. Department of Computer Science, Al-Aqsa University, P. O. Box 4051, Gaza, Palestine

    Mohammed A. Awadallah

  2. Department of Information Technology, Al-Huson University College, Al-Balqa Applied University, P.O. Box 50, Al-Huson, Irbid, Jordan

    Mohammed Azmi Al-Betar & Mahmud Alkoffash

  3. School of Computer Sciences, Universiti Sains Malaysia, 11800, Pulau Pinang, Malaysia

    Ahamad Tajudin Khader

  4. Department of Computer Science, University of Ilorin, Ilorin, Nigeria

    Asaju La’aro Bolaji

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  1. Mohammed A. Awadallah
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Awadallah, M.A., Al-Betar, M.A., Khader, A.T. et al. Hybridization of harmony search with hill climbing for highly constrained nurse rostering problem. Neural Comput & Applic 28, 463–482 (2017). https://doi.org/10.1007/s00521-015-2076-8

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