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Simulated Annealing for the Home Healthcare Routing and Scheduling Problem

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AIxIA 2022 – Advances in Artificial Intelligence (AIxIA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13796))

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Abstract

Home healthcare services are carried out by trained caregivers who visit the patient’s home, perform their service operations that depend on the patient’s need (e.g., medical care or just instrumental activities of daily living), and then move to the next patient.

We consider the home healthcare scheduling and routing problem, in the formulation proposed by Mankowska et al. (2014), which includes synchronization among services and time windows for patients. For this problem, we propose a local search approach based on a novel neighborhood operator and guided by the Simulated Annealing metaheuristic.

We show that our approach, properly tuned in a statistically-principled way, is able to outperform state-of-the-art methods on most of the original instances made available by Mankowska et al.

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Notes

  1. 1.

    All our results have been validated using the MIP model by Mankowska et al. [21], implemented and kindly supplied to us by Alberto Kummer.

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Acknowledgements

We wish to thank Alberto Kummer for answering our questions about the work of his research group and for providing us the CPLEX source code of the MIP model.

This research is part of the project “Models and algorithms for the optimization of integrated healthcare management” (no. 2020LNEZYC) supported by the Italian Ministry of University and Research (MUR) under the PRIN-2020 program.

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Authors and Affiliations

  1. DPIA, Università degli Studi di Udine, via delle Scienze 206, 33100, Udine, Italy

    Sara Ceschia, Luca Di Gaspero & Andrea Schaerf

Authors
  1. Sara Ceschia
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  2. Luca Di Gaspero
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  3. Andrea Schaerf
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Corresponding author

Correspondence to Andrea Schaerf .

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Editors and Affiliations

  1. University of Udine, Udine, Italy

    Agostino Dovier

  2. University of Udine, Udine, Italy

    Angelo Montanari

  3. National Research Council (CNR-ISTC), Rome, Italy

    Andrea Orlandini

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Ceschia, S., Di Gaspero, L., Schaerf, A. (2023). Simulated Annealing for the Home Healthcare Routing and Scheduling Problem. In: Dovier, A., Montanari, A., Orlandini, A. (eds) AIxIA 2022 – Advances in Artificial Intelligence. AIxIA 2022. Lecture Notes in Computer Science(), vol 13796. Springer, Cham. https://doi.org/10.1007/978-3-031-27181-6_28

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  • DOI: https://doi.org/10.1007/978-3-031-27181-6_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-27180-9

  • Online ISBN: 978-3-031-27181-6

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