IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/v39y2020i2d10.1007_s10878-019-00497-9.html
   My bibliography  Save this article

A patient flow scheduling problem in ophthalmology clinic solved by the hybrid EDA–VNS algorithm

Author

Listed:
  • Wenjuan Fan

    (Hefei University of Technology
    Hefei University of Technology)

  • Yi Wang

    (Hefei University of Technology
    Hefei University of Technology)

  • Tongzhu Liu

    (The First Affiliated Hospital of University of Science and Technology of China)

  • Guixian Tong

    (The First Affiliated Hospital of University of Science and Technology of China)

Abstract

This paper studies the patient flow scheduling problem in a multi-phase-multi-server system setting for a typical ophthalmology clinic, considering different patient flow processes and specific appointment time. In this problem, patients may go through the following processes, i.e., consultation, examination, re-consultation, and treatment, which form four patient flow paths according to different situations. The objective of this paper is to minimize the completion time of all the patients in the ophthalmology clinic. For solving this problem, we develop a hybrid meta-heuristic algorithm EDA–VNS combining estimation of distribution algorithm (EDA) and variable neighborhood search (VNS). We test the suitability of the approach for the ophthalmology clinic’s problem. Computational results demonstrate that the proposed algorithm is capable of providing high-quality solutions within a reasonable computational time. In addition, the proposed algorithm is also compared with several high-performing algorithms to validate its efficiency. The results indicate the advantages of the proposed EDA–VNS algorithm.

Suggested Citation

  • Wenjuan Fan & Yi Wang & Tongzhu Liu & Guixian Tong, 2020. "A patient flow scheduling problem in ophthalmology clinic solved by the hybrid EDA–VNS algorithm," Journal of Combinatorial Optimization, Springer, vol. 39(2), pages 547-580, February.
    • Handle: RePEc:spr:jcomop:v:39:y:2020:i:2:d:10.1007_s10878-019-00497-9
    DOI: 10.1007/s10878-019-00497-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-019-00497-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10878-019-00497-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bohui Liang & Ayten Turkcan & Mehmet Erkan Ceyhan & Keith Stuart, 2015. "Improvement of chemotherapy patient flow and scheduling in an outpatient oncology clinic," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7177-7190, December.
    2. Xiang Yi Zhang & Lu Chen, 2018. "A re-entrant hybrid flow shop scheduling problem with machine eligibility constraints," International Journal of Production Research, Taylor & Francis Journals, vol. 56(16), pages 5293-5305, August.
    3. Chern, Ching-Chin & Chien, Pei-Szu & Chen, Shu-Yi, 2008. "A heuristic algorithm for the hospital health examination scheduling problem," European Journal of Operational Research, Elsevier, vol. 186(3), pages 1137-1157, May.
    4. Chongjun Yan & Jiafu Tang & Bowen Jiang & Richard Y.K. Fung, 2015. "Sequential appointment scheduling considering patient choice and service fairness," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7376-7395, December.
    5. Ahmadi-Javid, Amir & Jalali, Zahra & Klassen, Kenneth J, 2017. "Outpatient appointment systems in healthcare: A review of optimization studies," European Journal of Operational Research, Elsevier, vol. 258(1), pages 3-34.
    6. Pei, Jun & Liu, Xinbao & Fan, Wenjuan & Pardalos, Panos M. & Lu, Shaojun, 2019. "A hybrid BA-VNS algorithm for coordinated serial-batching scheduling with deteriorating jobs, financial budget, and resource constraint in multiple manufacturers," Omega, Elsevier, vol. 82(C), pages 55-69.
    7. Hansen, Pierre & Mladenovic, Nenad, 2001. "Variable neighborhood search: Principles and applications," European Journal of Operational Research, Elsevier, vol. 130(3), pages 449-467, May.
    8. Puerto, Justo & Pérez-Brito, Dionisio & García-González, Carlos G., 2014. "A modified variable neighborhood search for the discrete ordered median problem," European Journal of Operational Research, Elsevier, vol. 234(1), pages 61-76.
    9. Xinbao Liu & Shaojun Lu & Jun Pei & Panos M. Pardalos, 2018. "A hybrid VNS-HS algorithm for a supply chain scheduling problem with deteriorating jobs," International Journal of Production Research, Taylor & Francis Journals, vol. 56(17), pages 5758-5775, September.
    10. Saremi, Alireza & Jula, Payman & ElMekkawy, Tarek & Wang, G. Gary, 2013. "Appointment scheduling of outpatient surgical services in a multistage operating room department," International Journal of Production Economics, Elsevier, vol. 141(2), pages 646-658.
    11. Lu, Yuwei & Xie, Xiaolan & Jiang, Zhibin, 2018. "Dynamic appointment scheduling with wait-dependent abandonment," European Journal of Operational Research, Elsevier, vol. 265(3), pages 975-984.
    12. Jing-nan Shen & Ling Wang & Huan-yu Zheng, 2016. "A modified teaching--learning-based optimisation algorithm for bi-objective re-entrant hybrid flowshop scheduling," International Journal of Production Research, Taylor & Francis Journals, vol. 54(12), pages 3622-3639, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jing Zhou, 2023. "Airline capacity distribution under financial budget and resource consideration," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-29, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gang Du & Xinyue Li & Hui Hu & Xiaoling Ouyang, 2018. "Optimizing Daily Service Scheduling for Medical Diagnostic Equipment Considering Patient Satisfaction and Hospital Revenue," Sustainability, MDPI, vol. 10(9), pages 1-23, September.
    2. Marynissen, Joren & Demeulemeester, Erik, 2019. "Literature review on multi-appointment scheduling problems in hospitals," European Journal of Operational Research, Elsevier, vol. 272(2), pages 407-419.
    3. Shuwan Zhu & Wenjuan Fan & Shanlin Yang & Jun Pei & Panos M. Pardalos, 2019. "Operating room planning and surgical case scheduling: a review of literature," Journal of Combinatorial Optimization, Springer, vol. 37(3), pages 757-805, April.
    4. Aditya Shetty & Harry Groenevelt & Vera Tilson, 2023. "Intraday dynamic rescheduling under patient no-shows," Health Care Management Science, Springer, vol. 26(3), pages 583-598, September.
    5. Bowen Jiang & Jiafu Tang & Chongjun Yan, 2019. "A comparison of fixed and variable capacity-addition policies for outpatient capacity allocation," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 150-182, January.
    6. Adam Diamant, 2021. "Dynamic multistage scheduling for patient-centered care plans," Health Care Management Science, Springer, vol. 24(4), pages 827-844, December.
    7. Hesaraki, Alireza F. & Dellaert, Nico P. & de Kok, Ton, 2019. "Generating outpatient chemotherapy appointment templates with balanced flowtime and makespan," European Journal of Operational Research, Elsevier, vol. 275(1), pages 304-318.
    8. Zhenyuan Liu & Jiongbing Lu & Zaisheng Liu & Guangrui Liao & Hao Howard Zhang & Junwu Dong, 2019. "Patient scheduling in hemodialysis service," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 337-362, January.
    9. Nur Banu Demir & Serhat Gul & Melih Çelik, 2021. "A stochastic programming approach for chemotherapy appointment scheduling," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(1), pages 112-133, February.
    10. T. Meersman & B. Maenhout, 2022. "Multi-objective optimisation for constructing cyclic appointment schedules for elective and urgent patients," Annals of Operations Research, Springer, vol. 312(2), pages 909-948, May.
    11. Miao Bai & Robert H. Storer & Gregory L. Tonkay, 2022. "Surgery Sequencing Coordination with Recovery Resource Constraints," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 1207-1223, March.
    12. S Vlah & Z Lukač & J Pacheco, 2011. "Use of VNS heuristics for scheduling of patients in hospital," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1227-1238, July.
    13. Hyun-Jung Alvarez-Oh & Hari Balasubramanian & Ekin Koker & Ana Muriel, 2018. "Stochastic Appointment Scheduling in a Team Primary Care Practice with Two Flexible Nurses and Two Dedicated Providers," Service Science, INFORMS, vol. 10(3), pages 241-260, September.
    14. Ahmadi-Javid, Amir & Jalali, Zahra & Klassen, Kenneth J, 2017. "Outpatient appointment systems in healthcare: A review of optimization studies," European Journal of Operational Research, Elsevier, vol. 258(1), pages 3-34.
    15. Hadid, Majed & Elomri, Adel & Mekkawy, Tarek El & Jouini, Oualid & Kerbache, Laoucine & Hamad, Anas, 2022. "Operations management of outpatient chemotherapy process: An optimization-oriented comprehensive review," Operations Research Perspectives, Elsevier, vol. 9(C).
    16. Alex Kuiper & Robert H. Lee, 2022. "Appointment Scheduling for Multiple Servers," Management Science, INFORMS, vol. 68(10), pages 7422-7440, October.
    17. Maedeh Fasihi & Reza Tavakkoli-Moghaddam & Fariborz Jolai, 2023. "A bi-objective re-entrant permutation flow shop scheduling problem: minimizing the makespan and maximum tardiness," Operational Research, Springer, vol. 23(2), pages 1-41, June.
    18. Xue Huang & Na Yin & Wei-Wei Liu & Ji-Bo Wang, 2020. "Common Due Window Assignment Scheduling with Proportional Linear Deterioration Effects," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 37(01), pages 1-15, January.
    19. Sharan Srinivas & A. Ravi Ravindran, 2020. "Designing schedule configuration of a hybrid appointment system for a two-stage outpatient clinic with multiple servers," Health Care Management Science, Springer, vol. 23(3), pages 360-386, September.
    20. Jun Pei & Qingru Song & Baoyu Liao & Xinbao Liu & Panos M. Pardalos, 2021. "Parallel-machine serial-batching scheduling with release times under the effects of position-dependent learning and time-dependent deterioration," Annals of Operations Research, Springer, vol. 298(1), pages 407-444, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jcomop:v:39:y:2020:i:2:d:10.1007_s10878-019-00497-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.