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A systematic two phase approach for the nurse rostering problem

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  • Valouxis, Christos
  • Gogos, Christos
  • Goulas, George
  • Alefragis, Panayiotis
  • Housos, Efthymios

Abstract

Nurse rostering is an NP-hard combinatorial problem which makes it extremely difficult to efficiently solve real life problems due to their size and complexity. Usually real problem instances have complicated work rules related to safety and quality of service issues in addition to rules about quality of life of the personnel. For the aforementioned reasons computer supported scheduling and rescheduling for the particular problem is indispensable. The specifications of the problem addressed were defined by the First International Nurse Rostering Competition (INRC2010) sponsored by the leading conference in the Automated Timetabling domain, PATAT-2010. Since the competition imposed quality and time constraint requirements, the problem instances were partitioned into sub-problems of manageable computational size and were then solved sequentially using Integer Mathematical Programming. A two phase strategy was implemented where in the first phase the workload for each nurse and for each day of the week was decided while in the second phase the specific daily shifts were assigned. In addition, local optimization techniques for searching across combinations of nurses’ partial schedules were also applied. This sequence is repeated several times depending on the available computational time. The results of our approach and the submitted software produced excellent solutions for both the known and the hidden problem instances, which in respect gave our team the first position in all tracks of the INRC-2010 competition.

Suggested Citation

  • Valouxis, Christos & Gogos, Christos & Goulas, George & Alefragis, Panayiotis & Housos, Efthymios, 2012. "A systematic two phase approach for the nurse rostering problem," European Journal of Operational Research, Elsevier, vol. 219(2), pages 425-433.
    • Handle: RePEc:eee:ejores:v:219:y:2012:i:2:p:425-433
    DOI: 10.1016/j.ejor.2011.12.042
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    2. Elín Björk Böðvarsdóttir & Niels-Christian Fink Bagger & Laura Elise Høffner & Thomas J. R. Stidsen, 2022. "A flexible mixed integer programming-based system for real-world nurse rostering," Journal of Scheduling, Springer, vol. 25(1), pages 59-88, February.
    3. Rahimian, Erfan & Akartunalı, Kerem & Levine, John, 2017. "A hybrid Integer Programming and Variable Neighbourhood Search algorithm to solve Nurse Rostering Problems," European Journal of Operational Research, Elsevier, vol. 258(2), pages 411-423.
    4. Florian Mischek & Nysret Musliu, 2019. "Integer programming model extensions for a multi-stage nurse rostering problem," Annals of Operations Research, Springer, vol. 275(1), pages 123-143, April.
    5. Toni I. Wickert & Alberto F. Kummer Neto & Márcio M. Boniatti & Luciana S. Buriol, 2021. "An integer programming approach for the physician rostering problem," Annals of Operations Research, Springer, vol. 302(2), pages 363-390, July.
    6. Suk Ho Jin & Ho Yeong Yun & Suk Jae Jeong & Kyung Sup Kim, 2017. "Hybrid and Cooperative Strategies Using Harmony Search and Artificial Immune Systems for Solving the Nurse Rostering Problem," Sustainability, MDPI, vol. 9(7), pages 1-19, June.
    7. Sophie Veldhoven & Gerhard Post & Egbert Veen & Tim Curtois, 2016. "An assessment of a days off decomposition approach to personnel shift scheduling," Annals of Operations Research, Springer, vol. 239(1), pages 207-223, April.
    8. David D. Cho & Kurt M. Bretthauer & Jan Schoenfelder, 2023. "Patient-to-nurse ratios: Balancing quality, nurse turnover, and cost," Health Care Management Science, Springer, vol. 26(4), pages 807-826, December.
    9. Peyman Kiani Nahand & Mahdi Hamid & Mahdi Bastan & Ali Mollajan, 2019. "Human resource management: new approach to nurse scheduling by considering human error," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(6), pages 1429-1443, December.
    10. Frederik Knust & Lin Xie, 2019. "Simulated annealing approach to nurse rostering benchmark and real-world instances," Annals of Operations Research, Springer, vol. 272(1), pages 187-216, January.
    11. Van den Bergh, Jorne & Beliën, Jeroen & De Bruecker, Philippe & Demeulemeester, Erik & De Boeck, Liesje, 2013. "Personnel scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 226(3), pages 367-385.
    12. Meignan, David & Knust, Sigrid, 2019. "A neutrality-based iterated local search for shift scheduling optimization and interactive reoptimization," European Journal of Operational Research, Elsevier, vol. 279(2), pages 320-334.
    13. Paola Cappanera & Filippo Visintin & Roberta Rossi, 2022. "The emergency department physician rostering problem: obtaining equitable solutions via network optimization," Flexible Services and Manufacturing Journal, Springer, vol. 34(4), pages 916-959, December.
    14. Farasat, Alireza & Nikolaev, Alexander G., 2016. "Signed social structure optimization for shift assignment in the nurse scheduling problem," Socio-Economic Planning Sciences, Elsevier, vol. 56(C), pages 3-13.
    15. Yang, Xiaopeng & Zheng, Danheng & Sieminowski, Tammy & Paradi, Joseph C., 2015. "A dynamic benchmarking system for assessing the recovery of inpatients: Evidence from the neurorehabilitation process," European Journal of Operational Research, Elsevier, vol. 240(2), pages 582-591.
    16. Haroldo G. Santos & Túlio A. M. Toffolo & Rafael A. M. Gomes & Sabir Ribas, 2016. "Integer programming techniques for the nurse rostering problem," Annals of Operations Research, Springer, vol. 239(1), pages 225-251, April.

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