The optimization of daily operating room surgery schedule can be problematic because of many constraints, like to determine the starting time of different surgeries and allocating the required resources, including the availability of surgical teams for complete surgical procedures. Recently, Answer Set Programming (ASP) has been successfully employed for addressing and solving real-life scheduling and planning problems in the healthcare domain. In this paper we present an enhanced solution using ASP for scheduling operating rooms taking explicitly into consideration availability of surgical teams, that include a surgeon and an anesthetist in different specialties for the entire duration of the surgery. We tested our solution on different benchmarks with realistic parameters for schedule’s length up to the target 5-days planning. The results of our experiments show that ASP is a suitable methodology for solving also such enhanced problem.

Solving Operating Room Scheduling Problems with Surgical Teams via Answer Set Programming

Dodaro C.;Khan M. K.;Maratea M.;Porro I.
2021-01-01

Abstract

The optimization of daily operating room surgery schedule can be problematic because of many constraints, like to determine the starting time of different surgeries and allocating the required resources, including the availability of surgical teams for complete surgical procedures. Recently, Answer Set Programming (ASP) has been successfully employed for addressing and solving real-life scheduling and planning problems in the healthcare domain. In this paper we present an enhanced solution using ASP for scheduling operating rooms taking explicitly into consideration availability of surgical teams, that include a surgeon and an anesthetist in different specialties for the entire duration of the surgery. We tested our solution on different benchmarks with realistic parameters for schedule’s length up to the target 5-days planning. The results of our experiments show that ASP is a suitable methodology for solving also such enhanced problem.
2021
978-3-030-77090-7
978-3-030-77091-4
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1103217
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