A model-based evolutionary algorithm for home health care scheduling

Yoram Clapper*, Joost Berkhout, René Bekker, Dennis Moeke

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

In this paper, for the first time a model-based evolutionary algorithm is presented for a real-life Home Health Care Routing and Scheduling Problem (HHCRSP). The algorithm generates routes consisting of care activities jointly with the underlying shift schedule, while taking into account the qualification levels. The performance is optimized in terms of travel time, time window waiting time and shift overtime. The algorithm is a novel extension of the permutation Gene-Pool Optimal Mixing Evolutionary Algorithm. Numerical experiments, using real-life data, show that the algorithm performs close to optimal for small instances, and outperforms schedules from a case study, leading to efficiency gains of 41%. Furthermore, it is shown that the model-based evolutionary algorithm performs better than a more traditional evolutionary algorithm, which demonstrates the importance of learning and exploiting a model to guide the optimization in HHCRSP.

Original languageEnglish
Article number106081
Pages (from-to)1-16
Number of pages16
JournalComputers and Operations Research
Volume150
Early online date13 Nov 2022
DOIs
Publication statusPublished - Feb 2023

Bibliographical note

Funding Information:
This research was funded by the Netherlands Organization for Scientific Research (NWO) under the Living Lab Sustainable Supply Chain Management in Healthcare project (project number: 439.18.457).

Publisher Copyright:
© 2022 The Author(s)

Funding

This research was funded by the Netherlands Organization for Scientific Research (NWO) under the Living Lab Sustainable Supply Chain Management in Healthcare project (project number: 439.18.457).

Keywords

  • Evolutionary algorithms
  • OR in health services
  • Routing
  • Scheduling

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