ABSTRACT
A core part of the rehabilitation scheduling process consists of planning rehabilitation physiotherapy sessions for patients, by assigning proper operators to them in a certain time slot of a given day, taking into account several legal, medical, and ethical requirements and optimizations, for example, patient's preferences and operator's work balancing. Being able to efficiently solve such problem is of upmost importance, in particular after the COVID-19 pandemic that significantly increased rehabilitation's needs. In this paper, we present a two-phase solution to rehabilitation scheduling based on Answer Set Programming, which proved to be an effective tool for solving practical scheduling problems. We first present a general encoding and then add domain-specific optimizations. Results of experiments performed on both synthetic and real benchmarks, the latter provided by ICS Maugeri, show the effectiveness of our solution as well as the impact of our domain-specific optimizations.
ABSTRACT
The rehabilitation scheduling process consists of planning rehabilitation physiotherapy sessions for patients, by assigning proper operators to them in a certain time slot of a given day, taking into account several requirements and optimizations, e.g. patient's preferences and operator's work balancing. Being able to efficiently solve such problem is of upmost importance, in particular as a consequence of the COVID-19 pandemic that significantly increased rehabilitation's needs. The problem has been recently successfully solved via a two-phase solution based on answer set programming (ASP). In this paper, we focus on the problem of rescheduling the rehabilitation sessions, which comes into play when the original schedule cannot be implemented, for reasons that involve the unavailability of operators and/or the absence of patients. We provide rescheduling solutions based on ASP for both phases, considering different scenarios. Results of experiments performed on real benchmarks, provided by ICS Maugeri, show that also the rescheduling problem can be solved in a satisfactory way. Finally, we present a web application that supports the usage of our solution.
ABSTRACT
The rehabilitation scheduling process consists of planning rehabilitation physiotherapy sessions for patients, by assigning proper operators to them in a certain time slot of a given day, taking into account several requirements and optimizations, e.g., patient’s preferences and operator’s work balancing. Being able to efficiently solve such problem is of upmost importance, in particular after the COVID-19 pandemic that significantly increased rehabilitation’s needs. In this paper, we present a solution to rehabilitation scheduling based on Answer Set Programming (ASP), which proved to be an effective tool for solving practical scheduling problems. Results of experiments performed on both synthetic and real benchmarks, the latter provided by ICS Maugeri, show the effectiveness of our solution. © 2021, Springer Nature Switzerland AG.
ABSTRACT
The ASP methodology has been recognized to be a viable solution to many practical applications, including scheduling problems, and in particular in the healthcare domain, of high interest in this period given the COVID-19 pandemic, where ASP proved to be an effective solution to some interesting problems. In this paper we present an overview of scheduling problems in the healthcare domain that have been successfully solved via ASP in the last two years. Starting from two”basic” problems, i.e., referred to the scheduling of operating rooms in presence of scarce resources (e.g., ICU beds) and the Nurse Scheduling problem, we show how we have improved such solutions, and mention further problems we have dealt with, including the Chemotherapy Scheduling problem. On top of all problems, we are working on providing explainability features, of utmost importance in this field, that for the moment are being instantiated on a single problem. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).