An Integrated Model of Green IoT and Vehicle Routing for Physician Attendance Scheduling in Home Care

Document Type : SI: DBBD-2023

Author

Guilan University of Medical science, Rasht, Iran

10.22059/ijms.2025.360013.675896

Abstract

With the advancement of technology, especially telemedicine and health care, information must meet the needs of people, especially people with low mobility, the elderly, and people who have difficulty accessing medical resources and services. These services must be accessed swiftly and dependably, prioritizing individual cases. One of the primary challenges in healthcare is routing and scheduling to cater to people's requirements. Various tools, including the Green Internet of Things, have the capability to gather information from patients and promptly transmit it to doctors and hospitals. Additionally, implementing green routing and reducing energy consumption through the Green Internet of Things can have environmental impacts. This article presents an integrated model of the Green Internet of Things and vehicle routing to schedule doctor visits in home healthcare. The objectives of this model are to minimize total costs and enhance customer satisfaction by utilizing information from the Green Internet of Things. Several factors are taken into account in this model, such as time windows, doctors' expertise, and the types of services requested by patients. The problem was addressed using MOGWO and NSGA II. The findings highlight that an increase in patient satisfaction leads to higher total costs for visits and vehicle routing. An analysis of 15 numerical examples across various scales demonstrated that the efficiency of MOGWO surpasses that of NSGA II and LP-Metric.

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Aliahmadi, A., Nozari, H. (2023). Evaluation of security metrics in AIoT and blockchain-based supply chain by Neutrosophic decision-making method. In Supply chain forum: an international journal, 24 (1), 31-42. https://doi.org/10.1080/16258312.2022.2101898
Alsharif, M. H., Jahid, A., Kelechi, A. H., & Kannadasan, R. (2023). Green IoT: A review and future research directions. Symmetry, 15(3), 757.https://doi.org/10.3390/sym15030757
Bahadori-Chinibelagh, S., Fathollahi-Fard, A. M., & Hajiaghaei-Keshteli, M. (2022). Two constructive algorithms to address a multi-depot home healthcare routing problem. IETE Journal of Research, 68(2), 1108-1114. https://doi.org/10.1080/03772063.2019.1642802
Euchi, J., Masmoudi, M., & Siarry, P. (2022). Home health care routing and scheduling problems: A literature review. 4OR, 20(3), 351-389.https://doi.org/10.1007/s10288-022-00516-2
Euchi, J., Zidi, S., & Laouamer, L. (2020). A hybrid approach to solve the vehicle routing problem with time windows and synchronized visits in-home health care. Arabian journal for science and engineering, 45, 10637-10652.https://doi.org/10.1007/s13369-020-04828-5
Fallah, M., & Nozari, H. (2021). Neutrosophic mathematical programming for optimization of multi-objective sustainable biomass supply chain network design. Computer Modeling in Engineering & Sciences, 129(2), 927-951.https://doi.org/10.32604/cmes.2021.017511
Fu, Y., Ding, F., Mu, Z., Sun, C., & Gao, K. (2022). Integrating scheduling and routing decisions into home health care operation with skill requirements and uncertainties. Journal of Simulation, 18(3), 259-282.https://doi.org/10.1080/17477778.2022.2108735
Ghahremani-Nahr, J., Aliahmadi, A., & Nozari, H. (2022). An IoT-based sustainable supply chain framework and blockchain. International Journal of Innovation in Engineering, 2(1), 12-21.https://doi.org/10.59615/ijie.2.1.12
Ghahremani-Nahr, J., Ghaderi, A., & Kian, R. (2023). A food bank network design examining food nutritional value and freshness: A multi objective robust fuzzy model. Expert Systems with Applications, 215, 119272.https://doi.org/10.1016/j.eswa.2022.119272
Ghiasvand Ghiasi, F., Yazdani, M., Vahdani, B., & Kazemi, A. (2022). Meta-Heuristic algorithms for multi-objective home health care routing and scheduling problem considering time windows and workload balance of nurses. Journal of Industrial Management Perspective, 12(1), 225-260.https://doi.org/10.52547/jimp.12.1.225
Goodarzian, F., Abraham, A., & Fathollahi-Fard, A. M. (2021). A bi-objective home health care logistics considering the working time and route balancing: A self-adaptive social engineering optimizer. Journal of Computational Design and Engineering, 8(1), 452-474.https://doi.org/10.1093/jcde/qwaa089
Legato, P., Mazza, R. M., & Fortino, G. (2022). A multi-level simulation-based optimization framework for IoT-enabled elderly care systems. Simulation Modelling Practice and Theory, 114, 102420.https://doi.org/10.1016/j.simpat.2021.102420
Ma, X., Fu, Y., Gao, K., Zhu, L., & Sadollah, A. (2023). A Multi-Objective scheduling and routing problem for home health care services via brain storm optimization. Complex System Modeling and Simulation, 3(1), 32-46. https://doi.org/10.23919/CSMS.2022.0025
Masmoudi, M., Jarboui, B., & Borchani, R. (2023). Efficient metaheuristics for the home (health)-care routing and scheduling problem with time windows and synchronized visits. Optimization Letters, 17(9), 2135-2167.https://doi.org/10.1007/s11590-023-02006-8
Mirabnejad, M., Jolai, F., Sazvar, Z., & Mirzabaghi, M. (2019). Home health care scheduling and routing with temporal dependencies and continuity of care. Advances in Industrial Engineering, 53(4), 209-228.https://doi.org/10.22059/jieng.2021.317379.1748
Movahed, A. B., Aliahmadi, A., Parsanejad, M., & Nozari, H. (2023). A systematic review of collaboration in supply chain 4.0 with meta-synthesis method. Supply Chain Analytics, 4, 100052.https://doi.org/10.1016/j.sca.2023.100052
Nikzad, E., Bashiri, M., & Abbasi, B. (2021). A matheuristic algorithm for stochastic home health care planning. European Journal of Operational Research, 288(3), 753-774.https://doi.org/10.1016/j.ejor.2020.06.040
Nozari, H., Tavakkoli-Moghaddam, R., Rohaninejad, M., & Hanzalek, Z. (2023, September). Artificial intelligence of things (AIoT) strategies for a smart sustainable-resilient supply chain. In IFIP International Conference on Advances in Production Management Systems (pp. 805-816). Cham: Springer Nature Switzerland.https://doi.org/10.1007/978-3-031-43670-3_56
Ratta, P., Kaur, A., Sharma, S., Shabaz, M., & Dhiman, G. (2021). Application of blockchain and internet of things in healthcare and medical sector: applications, challenges, and future perspectives. Journal of Food Quality, 2021(1), 7608296.https://doi.org/10.1155/2021/7608296
Rest, K. D., & Hirsch, P. (2022). Insights and decision support for home health care services in times of disasters. Central European journal of operations research, 30(1), 133-157.https://doi.org/10.1007/s10100-021-00770-5
Sangeetha, R. V., & Srinivasan, A. G. (2023, March). A decision-making system for dynamic scheduling and routing of mixed fleets with simultaneous synchronization in home health care. In Proceedings of Fourth International Conference on Communication, Computing and Electronics Systems: ICCCES 2022 (pp. 209-228). Springer Nature Singapore.https://doi.org/10.1007/978-981-19-7753-4_17
Shi, Y., Boudouh, T., & Grunder, O. (2017). A hybrid genetic algorithm for a home health care routing problem with time window and fuzzy demand. Expert Systems with Applications, 72, 160-176.https://doi.org/10.1016/j.eswa.2016.12.013
Shi, Y., Boudouh, T., & Grunder, O. (2019). A robust optimization for a home health care routing and scheduling problem with consideration of uncertain travel and service times. Transportation Research Part E: Logistics and Transportation Review, 128, 52-95.https://doi.org/10.1016/j.tre.2019.05.015
Szmelter-Jarosz, A., Ghahremani-Nahr, J., & Nozari, H. (2021). A neutrosophic fuzzy optimisation model for optimal sustainable closed-loop supply chain network during COVID-19. Journal of Risk and Financial Management, 14(11), 519.https://doi.org/10.3390/jrfm14110519
Taguchi, G., & Konishi, S. (1987). Taguchi methods: Orthogonal arrays and linear graphs: Tools for quality engineering. ASI press.
Torres, I. C., & Armas-Aguirre, J. (2021, December). Technological solution to improve outpatient medical care services using routing techniques and medical appointment scheduling. In 2021 IEEE 1st International Conference on Advanced Learning Technologies on Education & Research (ICALTER) (pp. 1-4). IEEE.https://doi.org/10.1109/ICALTER54105.2021.9675089
Xiang, T., Li, Y., & Szeto, W. Y. (2023). The daily routing and scheduling problem of home health care: Based on costs and participants’ preference satisfaction. International Transactions in Operational Research, 30(1), 39-69.https://doi.org/10.1111/itor.13043
Zhou, X., Yu, Z., Yuan, L., Wang, L., & Wu, C. (2020). Measuring accessibility of healthcare facilities for populations with multiple transportation modes considering residential transportation mode choice. ISPRS International Journal of Geo-Information, 9(6), 394.https://doi.org/10.3390/ijgi9060394