A New Model for Elderly Emotional Care Routing and Scheduling With Multi-Agency and the Combination of Nearby Services

References

• An, N., Yin, Y., Shi, H. S., Han, P., Cheng, S., Li, L. (2018). Building an ontology for eldercare service in China with a hierarchical clustering method. International Conference on Human-Computer Interaction, 10927:3–12.
   Google Scholar
• Braekers, K., Hartl, R. F., Parragh, S. N., & Tricoire, T. (2016). A bi-objective home care scheduling problem: Analyzing the trade-off between costs and client inconvenience. European Journal of Operational Research, 248(2), 428–443. https://doi.org/10.1016/j.ejor.2015.07.028
   Web of Science ®Google Scholar
• Cappanera, P., Scutella, M. G., Nervi, F., & Galli, L. (2018). Demand uncertainty in robust home care optimization. Omega, 80, 95–110. https://doi.org/10.1016/j.omega.2017.08.012
   Web of Science ®Google Scholar
• Carello, G., Lanzarone, E., & Mattia, S. (2018). Trade-off between stakeholders’ goals in the home care nurse-to-patient assignment problem. Operations Research for Health Care, 16, 29–40. https://doi.org/10.1016/j.orhc.2017.12.002
   Web of Science ®Google Scholar
• Cinar, A., Salman, F. S., & Bozkaya, B. (2021). Prioritized single nurse routing and scheduling for home healthcare services. European Journal of Operational Research, 289(3), 867–878. https://doi.org/10.1016/j.ejor.2019.07.009
   Web of Science ®Google Scholar
• Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 182–197. https://doi.org/10.1109/4235.996017
   Web of Science ®Google Scholar
• Erdem, M., & Bulkan, S. (2017). A two-stage solution approach for the large-scale home healthcare routeing and scheduling problem. South African Journal of Industrial Engineering, 28(4), 133–149. https://doi.org/10.7166/28-4-1754
   Web of Science ®Google Scholar
• Fathollahi-Fard, A. M., Ahmadi, A., Goodarzian, F., & Cheikhrouhou, N. (2020). A bi-objective home healthcare routing and scheduling problem considering patients' satisfaction in a fuzzy environment. Applied Soft Computing, 93, 106385. https://doi.org/10.1016/j.asoc.2020.106385
   PubMed Web of Science ®Google Scholar
• Fathollahi-Fard, A. M., Hajiaghaei-Keshteli, M., & Mirjalili, S. (2020). A set of efficient heuristics for a home healthcare problem. Neural Computing and Applications, 32(10), 6185–6205. https://doi.org/10.1007/s00521-019-04126-8
   Web of Science ®Google Scholar
• Fikar, C., & Hirsch, P. (2015). A matheuristic for routing real-world home service transport systems facilitating walking. Journal of Cleaner Production, 105, 300–310. https://doi.org/10.1016/j.jclepro.2014.07.013
   Web of Science ®Google Scholar
• Fikar, C., & Hirsch, P. (2017). Home health care routing and scheduling: A review. Computers & Operations Research, 77, 86–95. https://doi.org/10.1016/j.cor.2016.07.019
   Web of Science ®Google Scholar
• Frifita, S., Masmoudi, M., & Euchi, J. (2017). General variable neighborhood search for home health care routing and scheduling problem with time windows and synchronized visits. Electronic Notes in Discrete Mathematics, 58, 63–70. https://doi.org/10.1016/j.endm.2017.03.009
   Google Scholar
• Grenouilleau, F., Lahrichi, N., & Rousseau, L. M. (2020). New decomposition methods for home care scheduling with predefined visits. Computers & Operations Research, 115, 104855. https://doi.org/10.1016/j.cor.2019.104855
   Google Scholar
• Hiermann, G., Prandtstetter, M., Rendl, A., Puchinger, J., & Raidl, G. R. (2015). Metaheuristics for solving a multimodal home-healthcare scheduling problem. Central European Journal of Operations Research, 23(1), 89–113. https://doi.org/10.1007/s10100-013-0305-8
   Web of Science ®Google Scholar
• Jia, H. F., Sang, H., Luo, Q. Y., Yang, J., & Miao, H. Z. (2021). A cooperative evacuation strategy for mass passenger flow in urban rail transit transfer stations. International Journal of Modern Physics C, 32(1), 2150007. https://doi.org/10.1142/S0129183121500078
   Google Scholar
• Lanzarone, E., Matta, A., & Sahin, E. (2012). Operations management applied to home care services: The problem of assigning human resources to patients. IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, 42(6), 1346–1363. https://doi.org/10.1109/TSMCA.2012.2210207
   Web of Science ®Google Scholar
• Lee, U., Park, S., & Lee, I. (2020). Robust design optimization (RDO) of thermoelectric generator system using non-dominated sorting genetic algorithm II (NSGA-II). Energy, 196, 117090. https://doi.org/10.1016/j.energy.2020.117090
   Web of Science ®Google Scholar
• Lin, C. C., Hung, L. P., Liu, W. Y., & Tsai, M. C. (2018). Jointly rostering, routing, and rerostering for home health care services: A harmony search approach with genetic, saturation, inheritance, and immigrant schemes. Computers & Industrial Engineering, 115, 151–166. https://doi.org/10.1016/j.cie.2017.11.004
   Web of Science ®Google Scholar
• Lin, W. Y. (2020). Involvement of social workers in the community service provision system for the older people in urban China. Australian Social Work, 74(4), 1–16. https://doi.org/10.1080/0312407X.2020.1782447
   Web of Science ®Google Scholar
• Liu, R., Xie, X. L., Augusto, V., & Rodriguez, C. (2013). Heuristic algorithms for a vehicle routing problem with simultaneous delivery and pickup and time windows in home health care. European Journal of Operational Research, 230(3), 475–486. https://doi.org/10.1016/j.ejor.2013.04.044
   Web of Science ®Google Scholar
• Liu, R., Yuan, B., & Jiang, Z. B. (2017). Mathematical model and exact algorithm for the home care worker scheduling and routing problem with lunch break requirements. International Journal of Production Research, 55(2), 558–575. https://doi.org/10.1080/00207543.2016.1213917
   Web of Science ®Google Scholar
• Liu, R., Yuan, B., & Jiang, Z. B. (2020). The large-scale periodic home health care server assignment problem: A region-partition-based algorithm. IEEE Transactions on Automation Science and Engineering, 17(3), 1–1554. https://doi.org/10.1109/TASE.2020.2964101
   Web of Science ®Google Scholar
• Malagodi, L., Lanzarone, E., & Matta, A. (2021). Home care vehicle routing problem with chargeable overtime and strict and soft preference matching. Health Care Management Science, 24(1), 140–159. https://doi.org/10.1007/s10729-020-09532-2
   PubMed Web of Science ®Google Scholar
• Mendez-Fernandez, I., Lorenzo-Freire, S., García-Jurado, I., Costa, J., & Carpente, L. (2020). A heuristic approach to the task planning problem in a home care business. Health Care Management Science, 23(4), 556–570. https://doi.org/10.1007/s10729-020-09509-1
   PubMed Web of Science ®Google Scholar
• Miao, J., Wu, X. G., & Sun, X. (2019). Neighborhood, social cohesion, and the elderly's depression in Shanghai. Social Science & Medicine, 229, 134–143. https://doi.org/10.1016/j.socscimed.2018.08.022
   PubMed Web of Science ®Google Scholar
• Nasir, J., & Kuo, Y. (2020). A decision support framework for home health care transportation with simultaneous multi-vehicle routing and staff scheduling synchronization. Decision Support Systems, 138, 113361. https://doi.org/10.1016/j.dss.2020.113361
   Web of Science ®Google Scholar
• National Bureau of Statistics. (2021, May 11). Bulletin of the seventh national census (No. 5) – population age composition. http://www.stats.gov.cn/tjsj/tjgb/rkpcgb/qgrkpcgb/202106/t20210628_1818824.html
   Google Scholar
• Rasmussen, M. S., Justesen, T., Dohn, A., & Larsen, J. (2012). The Home Care Crew Scheduling Problem: Preference-based visit clustering and temporal dependencies. European Journal of Operational Research, 219(3), 598–610. https://doi.org/10.1016/j.ejor.2011.10.048
   Web of Science ®Google Scholar
• Restrepo, M. I., Rousseau, L. M., & Vallee, J. (2020). Home healthcare integrated staffing and scheduling. Omega, 95, 102057. https://doi.org/10.1016/j.omega.2019.03.015
   Google Scholar
• Sofia, A. S., & GaneshKumar, P. (2018). Multi-objective task scheduling to minimize energy consumption and makespan of cloud computing using NSGA-II. Journal of Network and Systems Management, 26(2), 463–485. https://doi.org/10.1007/s10922-017-9425-0
   Web of Science ®Google Scholar
• Sun, Y., & Shen, G. (2008). Improved NSGA-II multi-objective genetic algorithm based on hybridization-encouraged mechanism. Chinese Journal of Aeronautics, 21(6), 540–549. https://doi.org/10.1016/S1000-9361(08)60172-7
   Web of Science ®Google Scholar
• Wang, H. P., He, Y. K., Li, Y., & Wang, F. Y. (2020). Study on the home health caregiver scheduling problem under a resource sharing mode considering differences in working time and customer satisfaction. Discrete Dynamics in Nature and Society, 2020, 1–11. https://doi.org/10.1155/2020/7360765
   Google Scholar
• Wang, Q. (2016). 城市社区居家养老服务需求及其影响因素——基于全国性的城市老年人口调查数据 [Demands and determinations of community home-based care services for urban elderly: Based on the 2010 National elderly survey in China]. Population Research, 40(1), 98–112. https://kns.cnki.net/kcms/detail/detail.aspx?FileName=RKYZ201601008&DbName=CJFQ2016
   Google Scholar
• Wang, S. J., & Ma, S. (2018). Efficient methods for a bi-objective nursing home location and allocation problem: a case study. Applied Soft Computing, 65, 280–291. https://doi.org/10.1016/j.asoc.2018.01.014
   Web of Science ®Google Scholar
• Zhao, B. P., Xue, Y., Xu, B., Ma, T. H., & Liu, J. F. (2018). Multi-objective classification based on NSGA-II. International Journal of Computing Science and Mathematics, 9(6), 539–546. https://doi.org/10.1504/IJCSM.2018.096325
   Web of Science ®Google Scholar