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An ASP-based Solution to the Chemotherapy Treatment Scheduling problem

Published online by Cambridge University Press:  24 September 2021

CARMINE DODARO Open the ORCID record for CARMINE DODARO [Opens in a new window] ,
GIUSEPPE GALATÁ ,
ANDREA GRIONI ,
MARCO MARATEA Open the ORCID record for MARCO MARATEA [Opens in a new window] ,
MARCO MOCHI  and
IVAN PORRO
CARMINE DODARO
Affiliation:
University of Calabria, Italy (e-mail: [email protected])
GIUSEPPE GALATÁ
Affiliation:
SurgiQ srl, Italy (e-mail: [email protected])
ANDREA GRIONI
Affiliation:
San Martino Hospital, Italy (e-mail: [email protected])
MARCO MARATEA
Affiliation:
University of Genoa, Italy (e-mail: [email protected])
MARCO MOCHI
Affiliation:
University of Genoa, Italy (e-mail: [email protected])
IVAN PORRO
Affiliation:
SurgiQ srl, Italy (e-mail: [email protected])
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Abstract

The problem of scheduling chemotherapy treatments in oncology clinics is a complex problem, given that the solution has to satisfy (as much as possible) several requirements such as the cyclic nature of chemotherapy treatment plans, maintaining a constant number of patients, and the availability of resources, for example, treatment time, nurses, and drugs. At the same time, realizing a satisfying schedule is of upmost importance for obtaining the best health outcomes. In this paper we first consider a specific instance of the problem which is employed in the San Martino Hospital in Genova, Italy, and present a solution to the problem based on Answer Set Programming (ASP). Then, we enrich the problem and the related ASP encoding considering further features often employed in other hospitals, desirable also in S. Martino, and/or considered in related papers. Results of an experimental analysis, conducted on the real data provided by the San Martino Hospital, show that ASP is an effective solving methodology also for this important scheduling problem.

Keywords

healthcarechemotherapy treatment schedulinganswer set programming
Type
Original Article
Information
Theory and Practice of Logic Programming , Volume 21 , Special Issue 6: 37th International Conference on Logic Programming Special Issue II , November 2021 , pp. 835 - 851
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Copyright
© The Author(s), 2021. Published by Cambridge University Press

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