The Answer Set Programming (ASP) methodology has been recognized to be a viable solution to many practical applications, including scheduling problems in the Healthcare sector, where ASP proved to be an effective solution since 2017. In this paper, we present new scheduling problems in such field that have been successfully solved via ASP in the last few years. The interesting point is that some of these applications either deal with parts of the Healthcare process that were not previously addressed (i.e., the Pre-operative operations), or needed new solving approaches in order to be solved efficiently (i.e., the Chronic Outpatients problem solved via a Logic-Based Bender Decomposition method). For some of the problems discussed, we also provide preliminary experiments not appearing in previous publications on such problems. For all presented problems, we are also working on more "practical" issues, like solving rescheduling-related problems, providing explainability features, and implementing web applications for easy access to such solutions.

Recent Answer Set Programming Applications to Scheduling Problems in Digital Health / Cappanera P.; Caruso S.; Dodaro C.; Galata G.; Gavanelli M.; Maratea M.; Marte C.; Mochi M.; Nonato M.; Roma M.. - ELETTRONICO. - 3883:(2024), pp. 129-141. (Intervento presentato al convegno 1st International Workshop on Artificial Intelligence for Climate Change, 12th Italian Workshop on Planning and Scheduling, 31st RCRA Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion, and SPIRIT Workshop on Strategies, Prediction, Interaction, and Reasoning in Italy, AI4CC-IPS-RCRA-SPIRIT 2024).

Recent Answer Set Programming Applications to Scheduling Problems in Digital Health

Cappanera P.;
2024

Abstract

The Answer Set Programming (ASP) methodology has been recognized to be a viable solution to many practical applications, including scheduling problems in the Healthcare sector, where ASP proved to be an effective solution since 2017. In this paper, we present new scheduling problems in such field that have been successfully solved via ASP in the last few years. The interesting point is that some of these applications either deal with parts of the Healthcare process that were not previously addressed (i.e., the Pre-operative operations), or needed new solving approaches in order to be solved efficiently (i.e., the Chronic Outpatients problem solved via a Logic-Based Bender Decomposition method). For some of the problems discussed, we also provide preliminary experiments not appearing in previous publications on such problems. For all presented problems, we are also working on more "practical" issues, like solving rescheduling-related problems, providing explainability features, and implementing web applications for easy access to such solutions.
2024
CEUR Workshop Proceedings
1st International Workshop on Artificial Intelligence for Climate Change, 12th Italian Workshop on Planning and Scheduling, 31st RCRA Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion, and SPIRIT Workshop on Strategies, Prediction, Interaction, and Reasoning in Italy, AI4CC-IPS-RCRA-SPIRIT 2024
Cappanera P.; Caruso S.; Dodaro C.; Galata G.; Gavanelli M.; Maratea M.; Marte C.; Mochi M.; Nonato M.; Roma M.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1423912
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