The problem of scheduling Pre-Operative Assessment Clinic (PAC) consists of assigning patients to a day for the exams needed before a surgical procedure, taking into account patients with different priority levels, due dates, and operators availability. Realizing a satisfying schedule is of upmost importance for a clinic, since delay in PAC can cause delay in the subsequent phases, causing a decrease in patients’ satisfaction. In this paper, we divide the problem in two sub-problems: In the first sub-problem patients are assigned to a day taking into account a default list of exams; then, in the second sub-problem, having the actual list of exams needed by each patient, we use the results of the first sub-problem to assign a starting time to each exam. We first present a mathematical formulation for both problems. Then, we present solutions based on Answer Set Programming (ASP): The first solution is a genuine ASP encoding of the sub-problems, while the second introduces domain-specific optimizations. Experiments show that both solutions provide satisfying results in short time, while the second is able to prove optimality faster.
An ASP-Based Approach to Scheduling Pre-operative Assessment Clinic
Maratea M.;
2022-01-01
Abstract
The problem of scheduling Pre-Operative Assessment Clinic (PAC) consists of assigning patients to a day for the exams needed before a surgical procedure, taking into account patients with different priority levels, due dates, and operators availability. Realizing a satisfying schedule is of upmost importance for a clinic, since delay in PAC can cause delay in the subsequent phases, causing a decrease in patients’ satisfaction. In this paper, we divide the problem in two sub-problems: In the first sub-problem patients are assigned to a day taking into account a default list of exams; then, in the second sub-problem, having the actual list of exams needed by each patient, we use the results of the first sub-problem to assign a starting time to each exam. We first present a mathematical formulation for both problems. Then, we present solutions based on Answer Set Programming (ASP): The first solution is a genuine ASP encoding of the sub-problems, while the second introduces domain-specific optimizations. Experiments show that both solutions provide satisfying results in short time, while the second is able to prove optimality faster.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.