A heuristic approach to the task planning problem in a home care business
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A heuristic approach to the task planning problem in a home care businessAuthor(s)
Date
2020-12Citation
Méndez-Fernández, I., Lorenzo-Freire, S., García-Jurado, I. et al. A heuristic approach to the task planning problem in a home care business. Health Care Manag Sci 23, 556–570 (2020). https://doi.org/10.1007/s10729-020-09509-1
Abstract
[Abstract]: In this paper, we study a task scheduling problem in a home care business. The company has a set of supervisors in charge of scheduling the caregivers’ weekly plans. This can be a time-consuming task due to the large number of services they work with, as well as the need to consider user preferences, services required time windows and travel times between users’ homes. Apart from that, it is also important to have a continuity of care, i.e., that users generally prefer not to have their caregiver changed. This problem involves both route planning and employee task planning, which are usually very challenging. We first propose to model it using integer linear programming methodology. Since the real instances that the company needs to solve are very large, we design a heuristic algorithm, based on the simulated annealing philosophy, that allows the company to obtain the caregivers’ weekly schedules. Lastly, we check the algorithm’s good performance, by comparing the solutions it proposes with those provided by the integer linear programming methodology, in small size problems, and we present a case study to confirm that the algorithm correctly solves real-life instances. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
Keywords
Home care
Integer programming
Operations management
Operations research
Scheduling
Simulated annealing
Integer programming
Operations management
Operations research
Scheduling
Simulated annealing
Description
This version of the article has been accepted for publication, after peer review
(when applicable) and is subject to Springer Nature’s AM terms of use, but is not
the Version of Record and does not reflect post-acceptance improvements, or any
corrections. The Version of Record is available online at: https://
doi.org/10.1007/s10729-020-09509-1
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Copyright © 2020, Springer Science Business Media, LLC, part of Springer Nature
ISSN
1386-9620