Healthcare Systems. Группа авторов
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Number of caregivers | Number of patients | Computation time (s) |
2 | 2 4 8 | 1.58 3.27 5.09 |
4 | 4 8 16 | 7.43 10.60 12.44 |
8 | 8 16 32 | 13.80 14.38 16.73 |
16 | 16 32 64 | 18.62 20.01 22.69 |
Table 2.2. Case of rescheduling with disruptions
Number of disturbances | Number of reassigned visits per caregiver | Computation time (s) |
1 | 1 2 3 | 4.66-5.09 4.66-5.09 4.66-5.09 |
2 | 1 2 3 | 4.66-5.09 4.66-5.09 4.66-5.09 |
2 | 1 2 3 | 4.66-5.09 4.66-5.09 4.70-5.36 |
We also tested the rescheduling algorithm by adding disruptions represented by staff absences. The rescheduling phase can occur after the first route is calculated. Table 2.2 presents the results obtained when we have one to four disruptions. These visits are reassigned to other caregivers, and we find that each caregiver has one to three visits added to their initial schedule. Rescheduling is achieved in seconds. It is very efficient for the coordinator who needs a reactive system.
2.5. Conclusions and perspectives
In this chapter, we have focused on the HHC scheduling and rescheduling problems. We took into account the constraints related to the preferences, availabilities and dependency levels of patients as well as the qualifications and working hours of caregivers.
We have developed a genetic algorithm that calculates a schedule and also takes into account disruptions in real time. Re-planning makes it possible to reassign the unachieved activities in the case of an absence in a very short time (a few seconds). We were able to show the robustness and efficiency of our approach, which allows the scheduler manager to obtain all the schedule in few seconds, whether for the purposes of planning or rescheduling.
From the perspective of research, in future studies we will be able to integrate uncertainties related to the care duration as well as to take into account the rescheduling of other criteria, such as the absence of a patient at home or the development of their care condition.
2.6. References
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