Abstract
Nursing homes face the challenge to develop task assignment strategies that enable them to timely and efficiently meet the demand of their clients. In this contribution, we analyze a practice-based task scheduling problem with small time windows and care workers with different qualification levels. A set of care tasks has to be assigned to a given number of care workers with the objective of delivering the care as close as possible to the time preferences of the nursing home clients. To solve this problem, we propose a scheduling approach in which a Genetic Algorithm is combined with an Integer Linear Program. We verified the approach using numerical experiments. The next step will be to test the algorithm with reallife data and to implement it in practice.
| Original language | English |
|---|---|
| Article number | 5 |
| Pages (from-to) | 72-87 |
| Number of pages | 16 |
| Journal | Logistiek+ |
| Volume | 2019 |
| Issue number | 7 |
| Publication status | Published - 16 Apr 2019 |
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Bekker, R., Moeke, D., Dieleman, N., Buitink, M., den Uijl, J., Otsen, F., Koreman, K., & Passial, R. (2019). Demand-Driven Task-Scheduling in a Nursing Home Setting: A Genetic Algorithm Approach. Logistiek+, 2019(7), 72-87. Article 5. https://www.kennisdclogistiek.nl/publicaties/demand-driven-task-scheduling-in-a-nursing-home-setting-a-genetic-algorithm-approach
Bekker, Rene ; Moeke, Dennis ; Dieleman, Nanne et al. / Demand-Driven Task-Scheduling in a Nursing Home Setting : A Genetic Algorithm Approach. In: Logistiek+. 2019 ; Vol. 2019, No. 7. pp. 72-87.
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title = "Demand-Driven Task-Scheduling in a Nursing Home Setting: A Genetic Algorithm Approach",
abstract = "Nursing homes face the challenge to develop task assignment strategies that enable them to timely and efficiently meet the demand of their clients. In this contribution, we analyze a practice-based task scheduling problem with small time windows and care workers with different qualification levels. A set of care tasks has to be assigned to a given number of care workers with the objective of delivering the care as close as possible to the time preferences of the nursing home clients. To solve this problem, we propose a scheduling approach in which a Genetic Algorithm is combined with an Integer Linear Program. We verified the approach using numerical experiments. The next step will be to test the algorithm with reallife data and to implement it in practice.",
author = "Rene Bekker and Dennis Moeke and Nanne Dieleman and Martijn Buitink and {den Uijl}, Jarik and Floor Otsen and Kilian Koreman and Reven Passial",
year = "2019",
month = apr,
day = "16",
language = "English",
volume = "2019",
pages = "72--87",
journal = "Logistiek+",
publisher = "HAN Press",
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Bekker, R, Moeke, D, Dieleman, N, Buitink, M, den Uijl, J, Otsen, F, Koreman, K & Passial, R 2019, 'Demand-Driven Task-Scheduling in a Nursing Home Setting: A Genetic Algorithm Approach', Logistiek+, vol. 2019, no. 7, 5, pp. 72-87. <https://www.kennisdclogistiek.nl/publicaties/demand-driven-task-scheduling-in-a-nursing-home-setting-a-genetic-algorithm-approach>
Demand-Driven Task-Scheduling in a Nursing Home Setting: A Genetic Algorithm Approach. / Bekker, Rene; Moeke, Dennis; Dieleman, Nanne et al.
In: Logistiek+, Vol. 2019, No. 7, 5, 16.04.2019, p. 72-87.
Research output: Contribution to Journal › Article › Professional
TY - JOUR
T1 - Demand-Driven Task-Scheduling in a Nursing Home Setting
T2 - A Genetic Algorithm Approach
AU - Bekker, Rene
AU - Moeke, Dennis
AU - Dieleman, Nanne
AU - Buitink, Martijn
AU - den Uijl, Jarik
AU - Otsen, Floor
AU - Koreman, Kilian
AU - Passial, Reven
PY - 2019/4/16
Y1 - 2019/4/16
N2 - Nursing homes face the challenge to develop task assignment strategies that enable them to timely and efficiently meet the demand of their clients. In this contribution, we analyze a practice-based task scheduling problem with small time windows and care workers with different qualification levels. A set of care tasks has to be assigned to a given number of care workers with the objective of delivering the care as close as possible to the time preferences of the nursing home clients. To solve this problem, we propose a scheduling approach in which a Genetic Algorithm is combined with an Integer Linear Program. We verified the approach using numerical experiments. The next step will be to test the algorithm with reallife data and to implement it in practice.
AB - Nursing homes face the challenge to develop task assignment strategies that enable them to timely and efficiently meet the demand of their clients. In this contribution, we analyze a practice-based task scheduling problem with small time windows and care workers with different qualification levels. A set of care tasks has to be assigned to a given number of care workers with the objective of delivering the care as close as possible to the time preferences of the nursing home clients. To solve this problem, we propose a scheduling approach in which a Genetic Algorithm is combined with an Integer Linear Program. We verified the approach using numerical experiments. The next step will be to test the algorithm with reallife data and to implement it in practice.
M3 - Article
VL - 2019
SP - 72
EP - 87
JO - Logistiek+
JF - Logistiek+
IS - 7
M1 - 5
ER -
Bekker R, Moeke D, Dieleman N, Buitink M, den Uijl J, Otsen F et al. Demand-Driven Task-Scheduling in a Nursing Home Setting: A Genetic Algorithm Approach. Logistiek+. 2019 Apr 16;2019(7):72-87. 5.
