Time Window NSGA-II Route Planning Algorithm for Home Care Appointment Scheduling in the Elderly Industry

Given the lack of healthcare resources, the home care sector faces a serious challenge in figuring out how to maximize the effectiveness of healthcare employees' services and raise consumer satisfaction. In this study, a model for healthcare worker scheduling and path planning is built. Fuzzy time window theory is used to discuss how to determine service duration and fuzzy service duration sub-situations. A path-planning algorithm based on a non-dominated ranking genetic algorithm is used to optimize the decision-making process. To analyze the aspects that affect the results of the model runs and use them as a foundation for effective planning recommendations, simulation experiments based on real data were conducted. According to the findings, customer demand under a defined service hour reaches a threshold of 343 before additional man-hour expenses starts to accrue. Decision-makers must therefore make adequate staffing modifications before this happens. The appointment time window has a greater impact on customer satisfaction and can be suitably extended in the customer appointment interface to raise satisfaction. The -value, which can be calculated based on the carer's fuzzy service hours, high and low peak demand, and the percentage of urgent tasks, is related to the time cost and satisfaction under fuzzy service hours. The corresponding optimal -values are 0.6, 0.3, 0.6, and 0.6, which can balance the time cost and customer satisfaction in this scenario.

@article{Xie2024,
  title     = {Time Window NSGA-II Route Planning Algorithm for Home Care Appointment Scheduling in the Elderly Industry},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {6},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Guoping Xie},
  doi       = {10.14569/IJACSA.2024.01506134},
  url       = {https://doi.org/10.14569/IJACSA.2024.01506134}
}