| Summary: | 碩士 === 國立交通大學 === 工業工程與管理系所 === 106 === As the era of population aging, the home health care problems have become more and more attention. In recent years, in addition to solving the Nurse rostering problem and vehicle routing problem, more and more studies have been conducted to improve patient satisfaction by considering the patient's preference for the home care worker. However, most of home care workers for schedule did not consider the lack of the difference in the degree of attention between the items of the patient's preference for the home care worker in the previous work. Therefore, this dissertation proposes Home Health Care Rostering and Routing Problem with Matching Score of Caregivers and Caretakers. Considering the patient’s preference for the home care worker and making the preference items have different levels of emphasis, and calculate the matching score between the patient and the home care worker. That the nurse who more in line with the patient's preferences has a higher probability to perform the task. The study is planning a weekly schedule for home care workers with the goal of minimizing costs and maximizing patient and home care worker satisfaction and caregiver satisfaction under constraints of skills qualifications, regulations, and link time. Because the home health care rostering and routing problem is the NP-hard problem，and the two sub-problems home care worker rostering and vehicle routing problems with time windows are also NP-hard problems. It is suitable to solve by heuristic algorithm. Due to the excellent performance of genetic algorithms (GA) in past scheduling studies, and the variable neighborhood search method (VNS) has also been proved to be more suitable for solving the vehicle routing problems with time windows than other algorithms, exactly the same with the two sub-problems of our problems. So this paper proposes a joint GA and VNS, divided the problem into two stages to solve. Using GA to solve the home care worker rostering, VNS to solve the vehicle routing problems with time windows. The experimental results show that the matching mechanism of patients and home care workers proposed in this study can effectively improve patient satisfaction; the combined GA and VNS can be obtained more stable and better results than other algorithms in different instances.
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