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An ASP-based Solution for Operating Room Scheduling with Beds Management

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Rules and Reasoning (RuleML+RR 2019)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11784))

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Abstract

The Operating Room Scheduling (ORS) problem is the task of assigning patients to operating rooms, taking into account different specialties, lengths and priority scores of each planned surgery, operating room session durations, and the availability of beds for the entire length of stay both in the Intensive Care Unit and in the wards. A proper solution to the ORS problem is of utmost importance for the quality of the health-care and the satisfaction of patients in hospital environments. In this paper we present an improved solution to the problem based on Answer Set Programming (ASP) that, differently from a recent one, takes explictly into account beds management. Results of an experimental analysis, conducted on benchmarks with realistic sizes and parameters, show that ASP is a suitable solving methodology for solving also such improved problem version.

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Author information

Authors and Affiliations

  1. DEMACS, University of Calabria, Rende, Italy

    Carmine Dodaro

  2. SurgiQ srl, Genova, Italy

    Giuseppe Galatà & Ivan Porro

  3. DIBRIS, University of Genova, Genova, Italy

    Muhammad Kamran Khan & Marco Maratea

Authors
  1. Carmine Dodaro
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  2. Giuseppe Galatà
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  3. Muhammad Kamran Khan
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  4. Marco Maratea
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  5. Ivan Porro
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Corresponding author

Correspondence to Marco Maratea .

Editor information

Editors and Affiliations

  1. Stony Brook University, Stony Brook, NY, USA

    Paul Fodor

  2. Free University of Bozen-Bolzano, Bolzano, Italy

    Marco Montali

  3. Free University of Bozen-Bolzano, Bolzano, Italy

    Diego Calvanese

  4. SINTEF AS, Oslo, Norway

    Dumitru Roman

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Dodaro, C., Galatà, G., Khan, M.K., Maratea, M., Porro, I. (2019). An ASP-based Solution for Operating Room Scheduling with Beds Management. In: Fodor, P., Montali, M., Calvanese, D., Roman, D. (eds) Rules and Reasoning. RuleML+RR 2019. Lecture Notes in Computer Science(), vol 11784. Springer, Cham. https://doi.org/10.1007/978-3-030-31095-0_5

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  • DOI: https://doi.org/10.1007/978-3-030-31095-0_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-31094-3

  • Online ISBN: 978-3-030-31095-0

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