IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/v45y2023i2d10.1007_s10878-023-01000-1.html
   My bibliography  Save this article

Multi-objective outpatient scheduling in health centers considering resource constraints and service quality: a robust optimization approach

Author

Listed:
  • J. Behnamian

    (Bu-Ali Sina University)

  • Z. Gharabaghli

    (Bu-Ali Sina University)

Abstract

Hospitals are among the largest and most sophisticated service organizations and the most critical service delivery units in the health system. Due to the high risk of hospital services, the services provided must be of acceptable quality. Also, patient scheduling and timely receiving of services in medical centers can lead to patient satisfaction. In this study, a patient admission scheduling is modeled in which it is assumed that the staff is not always available. To enhance the quality of healthcare services and increases patient satisfaction, in this research, mathematical modeling is presented, in which resource capacity and treatment sequence constraints are considered in the proposed model. Furthermore, the uncertainty in the service quality parameter is taken into account, which makes the model more realistic. In this regard, first, a robust optimization approach based on the Bertsimas and Sim model is applied. Then, due to its Np-hardness, the multi-objective particle swarm optimization algorithm is proposed. Finally, the quality of the proposed algorithm is examined by comparing its results with the GAMS solver and the NSGA-II algorithm in small and large-size instances, respectively. Results indicate the proper performance of the proposed algorithm.

Suggested Citation

  • J. Behnamian & Z. Gharabaghli, 2023. "Multi-objective outpatient scheduling in health centers considering resource constraints and service quality: a robust optimization approach," Journal of Combinatorial Optimization, Springer, vol. 45(2), pages 1-35, March.
    • Handle: RePEc:spr:jcomop:v:45:y:2023:i:2:d:10.1007_s10878-023-01000-1
    DOI: 10.1007/s10878-023-01000-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-023-01000-1
    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/s10878-023-01000-1?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. Christiane Barz & Kumar Rajaram, 2015. "Elective Patient Admission and Scheduling under Multiple Resource Constraints," Production and Operations Management, Production and Operations Management Society, vol. 24(12), pages 1907-1930, December.
    2. Huiqiao Su & Guohua Wan & Shan Wang, 2019. "Online scheduling for outpatient services with heterogeneous patients and physicians," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 123-149, January.
    3. Lili Liu & Guochun Tang & Baoqiang Fan & Xingpeng Wang, 2015. "Two-person cooperative games on scheduling problems in outpatient pharmacy dispensing process," Journal of Combinatorial Optimization, Springer, vol. 30(4), pages 938-948, November.
    4. Wang, Yu & Zhang, Yu & Tang, Jiafu, 2019. "A distributionally robust optimization approach for surgery block allocation," European Journal of Operational Research, Elsevier, vol. 273(2), pages 740-753.
    5. A. G. Leeftink & I. M. H. Vliegen & E. W. Hans, 2019. "Stochastic integer programming for multi-disciplinary outpatient clinic planning," Health Care Management Science, Springer, vol. 22(1), pages 53-67, March.
    6. A. Ben-Tal & A. Nemirovski, 1998. "Robust Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 23(4), pages 769-805, November.
    7. Xuanzhu Fan & Jiafu Tang & Chongjun Yan & Hainan Guo & Zhongfa Cao, 2021. "Outpatient appointment scheduling problem considering patient selection behavior: data modeling and simulation optimization," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 677-699, November.
    8. Ying Yang & Shoucheng Luo & Jing Fan & Xinye Zhou & Chunyu Fu & Guochun Tang, 2019. "Study on specialist outpatient matching appointment and the balance matching model," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 20-39, January.
    9. Shehadeh, Karmel S. & Cohn, Amy E.M. & Jiang, Ruiwei, 2020. "A distributionally robust optimization approach for outpatient colonoscopy scheduling," European Journal of Operational Research, Elsevier, vol. 283(2), pages 549-561.
    10. Maiyar, Lohithaksha M & Thakkar, Jitesh J, 2019. "Environmentally conscious logistics planning for food grain industry considering wastages employing multi objective hybrid particle swarm optimization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 220-248.
    11. Shoshana Hahn-Goldberg & Michael Carter & J. Beck & Maureen Trudeau & Philomena Sousa & Kathy Beattie, 2014. "Dynamic optimization of chemotherapy outpatient scheduling with uncertainty," Health Care Management Science, Springer, vol. 17(4), pages 379-392, December.
    12. Nikky Kortbeek & M. F. van der Velde & N. Litvak, 2017. "Organizing multidisciplinary care for children with neuromuscular diseases at the Academic Medical Center, Amsterdam," Health Systems, Taylor & Francis Journals, vol. 6(3), pages 209-225, November.
    13. 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.
    Full references (including those not matched with items on IDEAS)

    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. Jing Fan & Hui Shi, 0. "A three-stage supply chain scheduling problem based on the nursing assistants’ daily work in a hospital," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-13.
    2. Novak, Antonin & Gnatowski, Andrzej & Sucha, Premysl, 2022. "Distributionally robust scheduling algorithms for total flow time minimization on parallel machines using norm regularizations," European Journal of Operational Research, Elsevier, vol. 302(2), pages 438-455.
    3. Jing Yu & Lining Xing & Xu Tan, 0. "The new treatment mode research of hepatitis B based on ant colony algorithm," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-20.
    4. Guo, Xiaotong & Caros, Nicholas S. & Zhao, Jinhua, 2021. "Robust matching-integrated vehicle rebalancing in ride-hailing system with uncertain demand," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 161-189.
    5. Majed Hadid & Adel Elomri & Regina Padmanabhan & Laoucine Kerbache & Oualid Jouini & Abdelfatteh El Omri & Amir Nounou & Anas Hamad, 2022. "Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling," IJERPH, MDPI, vol. 19(23), pages 1-34, November.
    6. Sean Harris & David Claudio, 2022. "Current Trends in Operating Room Scheduling 2015 to 2020: a Literature Review," SN Operations Research Forum, Springer, vol. 3(1), pages 1-42, March.
    7. Jing Fan & Hui Shi, 2021. "A three-stage supply chain scheduling problem based on the nursing assistants’ daily work in a hospital," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 896-908, November.
    8. Aisha Tayyab & Saif Ullah & Mohammed Fazle Baki, 2023. "An Outer Approximation Method for Scheduling Elective Surgeries with Sequence Dependent Setup Times to Multiple Operating Rooms," Mathematics, MDPI, vol. 11(11), pages 1-15, May.
    9. Novak, Antonin & Sucha, Premysl & Novotny, Matej & Stec, Richard & Hanzalek, Zdenek, 2022. "Scheduling jobs with normally distributed processing times on parallel machines," European Journal of Operational Research, Elsevier, vol. 297(2), pages 422-441.
    10. Shehadeh, Karmel S. & Padman, Rema, 2021. "A distributionally robust optimization approach for stochastic elective surgery scheduling with limited intensive care unit capacity," European Journal of Operational Research, Elsevier, vol. 290(3), pages 901-913.
    11. Bakker, Hannah & Dunke, Fabian & Nickel, Stefan, 2020. "A structuring review on multi-stage optimization under uncertainty: Aligning concepts from theory and practice," Omega, Elsevier, vol. 96(C).
    12. 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.
    13. Lu, Haimin & Pei, Zhi, 2023. "Single machine scheduling with release dates: A distributionally robust approach," European Journal of Operational Research, Elsevier, vol. 308(1), pages 19-37.
    14. Mo, Baichuan & Koutsopoulos, Haris N. & Shen, Zuo-Jun Max & Zhao, Jinhua, 2023. "Robust path recommendations during public transit disruptions under demand uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 169(C), pages 82-107.
    15. Jing Yu & Lining Xing & Xu Tan, 2021. "The new treatment mode research of hepatitis B based on ant colony algorithm," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 740-759, November.
    16. Wenqing Chen & Melvyn Sim & Jie Sun & Chung-Piaw Teo, 2010. "From CVaR to Uncertainty Set: Implications in Joint Chance-Constrained Optimization," Operations Research, INFORMS, vol. 58(2), pages 470-485, April.
    17. Stefan Mišković, 2017. "A VNS-LP algorithm for the robust dynamic maximal covering location problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 1011-1033, October.
    18. Chuong, T.D. & Jeyakumar, V., 2017. "Convergent hierarchy of SDP relaxations for a class of semi-infinite convex polynomial programs and applications," Applied Mathematics and Computation, Elsevier, vol. 315(C), pages 381-399.
    19. Chassein, André & Dokka, Trivikram & Goerigk, Marc, 2019. "Algorithms and uncertainty sets for data-driven robust shortest path problems," European Journal of Operational Research, Elsevier, vol. 274(2), pages 671-686.
    20. Dranichak, Garrett M. & Wiecek, Margaret M., 2019. "On highly robust efficient solutions to uncertain multiobjective linear programs," European Journal of Operational Research, Elsevier, vol. 273(1), pages 20-30.

    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:45:y:2023:i:2:d:10.1007_s10878-023-01000-1. 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.