The Patient Admission Scheduling problem consists in scheduling patients within a planning horizon into hospital rooms in such a way to maximize medical treatment effectiveness, management efficiency, and patient's comfort.
In this talk, we discuss, revisit, and extend the Patient Admission Scheduling problem proposed in the literature, in order to make it suitable for practical applications. We propose a solution approach based on local search, which explores the search space using a composite neighborhood. In addition, we discuss an instance generator that uses real-world data and statistical distributions so as to synthesize realistic and challenging case studies. Finally, we discuss the experimental activity including statistically-principled parameter tuning methods, for both the static and the dynamic version of the problem.
Andrea Schaerf received his master degree cum laude in Electrical Engineering in 1990 and his PhD in Computer Science in 1994 from University of Rome "La Sapienza". During his studies, he spent one year at Stanford University (California, U.S.A.) under the supervision of Y. Shoham. After graduating, he was supported for one year by a scholarship from CNR, and successively he spent one year at CWI in Amsterdam under the supervision of K. Apt, supported by a fellowship by ERCIM. From 1996 to 1998 he has been Assistant Professor at University of Rome "La Sapienza". From 1998 to 2005 he has been Associate Professor at University of Udine, where, starting November 2005, he is Full Professor. His main research interest is in algorithms, specification languages, and software tools for scheduling and timetabling problems.
This talk is organized by the Vienna PhD School of Informatics and part of the lecture series "Current Trends in Computer Science".