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Scheduling Optimization of Home Health Care Service Considering Patients’ Priorities and Time Windows

Author

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  • Gang Du

    (Department of Business Management, School of Business Administration, Faculty of Economics and Management, East China Normal University, Shanghai 200062, China)

  • Xi Liang

    (Department of Business Management, School of Business Administration, Faculty of Economics and Management, East China Normal University, Shanghai 200062, China)

  • Chuanwang Sun

    (China Center for Energy Economics Research, School of Economics, Xiamen University, Xiamen 361005, China
    Department of International Economics and Business, School of Economics, Xiamen University, Xiamen 361005, China)

Abstract

As a new service model, home health care can provide effective health care by adopting door-to-door service. The reasonable arrangements for nurses and their routes not only can reduce medical expenses, but also can enhance patient satisfaction. This research focuses on the home health care scheduling optimization problem with known demands and service capabilities. Aimed at minimizing the total cost, an integer programming model was built in this study, which took both the priorities of patients and constraints of time windows into consideration. The genetic algorithm with local search was used to solve the proposed model. Finally, a case study of Shanghai, China, was conducted for the empirical analysis. The comparison results verify the effectiveness of the proposed model and methodology, which can provide the decision support for medical administrators of home health care.

Suggested Citation

  • Gang Du & Xi Liang & Chuanwang Sun, 2017. "Scheduling Optimization of Home Health Care Service Considering Patients’ Priorities and Time Windows," Sustainability, MDPI, vol. 9(2), pages 1-22, February.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:2:p:253-:d:89973
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    Cited by:

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    2. Gang Du & Luyao Zheng & Xiaoling Ouyang, 2019. "Real-time scheduling optimization considering the unexpected events in home health care," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 196-220, January.
    3. Biao Yuan & Zhibin Jiang, 2017. "Disruption Management for the Real-Time Home Caregiver Scheduling and Routing Problem," Sustainability, MDPI, vol. 9(12), pages 1-15, November.
    4. Rym Ben Bachouch & Jihène Tounsi & Chouari Borhen, 2020. "Home health care scheduling activities," Post-Print hal-03229580, HAL.
    5. Kwok Tai Chui & Wadee Alhalabi & Sally Shuk Han Pang & Patricia Ordóñez de Pablos & Ryan Wen Liu & Mingbo Zhao, 2017. "Disease Diagnosis in Smart Healthcare: Innovation, Technologies and Applications," Sustainability, MDPI, vol. 9(12), pages 1-23, December.
    6. Li, Yanfeng & Xiang, Ting & Szeto, Wai Yuen, 2021. "Home health care routing and scheduling problem with the consideration of outpatient services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    7. 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.
    8. Jalel Euchi & Malek Masmoudi & Patrick Siarry, 2022. "Home health care routing and scheduling problems: a literature review," 4OR, Springer, vol. 20(3), pages 351-389, September.
    9. Jamal Abdul Nasir & Chuangyin Dang, 2018. "Solving a More Flexible Home Health Care Scheduling and Routing Problem with Joint Patient and Nursing Staff Selection," Sustainability, MDPI, vol. 10(1), pages 1-22, January.
    10. Aleksandra Marcikic Horvat & Branislav Dudic & Boris Radovanov & Boban Melovic & Otilija Sedlak & Monika Davidekova, 2020. "Binary Programming Model for Rostering Ambulance Crew-Relevance for the Management and Business," Mathematics, MDPI, vol. 9(1), pages 1-13, December.
    11. Mustafa Demirbilek & Juergen Branke & Arne K. Strauss, 2021. "Home healthcare routing and scheduling of multiple nurses in a dynamic environment," Flexible Services and Manufacturing Journal, Springer, vol. 33(1), pages 253-280, March.

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