An ASP-based Solution to the Chemotherapy Treatment Scheduling problem

TL;DR

This paper presents an ASP-based approach to optimize chemotherapy scheduling in hospitals, addressing complex constraints to improve treatment plans and resource utilization, validated on real hospital data.

Contribution

It introduces a novel ASP encoding for chemotherapy scheduling and extends it to incorporate additional real-world features, demonstrating effectiveness on actual hospital data.

Findings

ASP effectively solves complex scheduling constraints

The approach improves resource utilization in chemotherapy planning

Validated on real hospital data from San Martino Hospital

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, e.g., 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. Under consideration for acceptance in TPLP.