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Nature-Inspired Chemical Reaction Optimisation Algorithm for Handling Nurse Rostering Problem

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Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems - Volume 2

Part of the book series: Proceedings in Adaptation, Learning and Optimization ((PALO,volume 2))

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Abstract

The optimisation of the nurse rostering problem is chosen in this work seeking to improve the organization of hospital duties and to elevate health care by enhancing the quality of the decision-making process. Nurse rostering is a difficult and complex problem with a large number of demands and requirements that conflict with hospital workload constraints in terms of employee work regulations and personal preferences. We propose a variable population-based metaheuristic algorithm, the chemical reaction optimisation (CRO), to solve the NRP at the First International Nurse Rostering Competition (2010). The CRO algorithm features an adaptive search procedure that systematically controls the selection between an intensive search strategy and diversification search based on specific criteria to reach the best solution. Computational results were measured with three complexity levels as a total of 30 variant instances based on real-world constraints.

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Authors and Affiliations

  1. Data Mining and Optimisation Research Group (DMO), Centre for Artificial Intelligence Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Yahya Z. Arajy & Salwani Abdullah

Authors
  1. Yahya Z. Arajy
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  2. Salwani Abdullah
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Corresponding author

Correspondence to Yahya Z. Arajy .

Editor information

Editors and Affiliations

  1. Faculty of Science and Technology Department of Infomatics, Kindai University, Higashi-Osaka, Japan

    Hisashi Handa

  2. Department of Computer Science and Intelligent Systems, Osaka Prefecture University, Osaka, Japan

    Hisao Ishibuchi

  3. School of Computer Engineering, Nanyang Technological University, Singapore, Singapore

    Yew-Soon Ong

  4. Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore

    Kay-Chen Tan

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Arajy, Y.Z., Abdullah, S. (2015). Nature-Inspired Chemical Reaction Optimisation Algorithm for Handling Nurse Rostering Problem. In: Handa, H., Ishibuchi, H., Ong, YS., Tan, KC. (eds) Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems - Volume 2. Proceedings in Adaptation, Learning and Optimization, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-13356-0_43

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  • DOI: https://doi.org/10.1007/978-3-319-13356-0_43

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13355-3

  • Online ISBN: 978-3-319-13356-0

  • eBook Packages: EngineeringEngineering (R0)

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