{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T14:31:37Z","timestamp":1762353097946,"version":"3.40.5"},"reference-count":40,"publisher":"Cambridge University Press (CUP)","issue":"2","license":[{"start":{"date-parts":[[2021,7,14]],"date-time":"2021-07-14T00:00:00Z","timestamp":1626220800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":["cambridge.org"],"crossmark-restriction":true},"short-container-title":["Theory and Practice of Logic Programming"],"published-print":{"date-parts":[[2022,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The Operating Room Scheduling (ORS) problem is the task of assigning patients to operating rooms (ORs), taking into account different specialties, lengths, and priority scores of each planned surgery, OR session durations, and the availability of beds for the entire length of stay (LOS) both in the Intensive Care Unit (ICU) and in the wards. A proper solution to the ORS problem is of primary importance for the healthcare service quality and the satisfaction of patients in hospital environments. In this paper we first present a solution to the problem based on Answer Set Programming (ASP). The solution is tested on benchmarks with realistic sizes and parameters, on three scenarios for the target length on 5-day scheduling, common in small\u2013medium-sized hospitals, and results show that ASP is a suitable solving methodology for the ORS problem in such setting. Then, we also performed a scalability analysis on the schedule length up to 15 days, which still shows the suitability of our solution also on longer plan horizons. Moreover, we also present an ASP solution for the rescheduling problem, that is, when the offline schedule cannot be completed for some reason. Finally, we introduce a web framework for managing ORS problems via ASP that allows a user to insert the main parameters of the problem, solve a specific instance, and show results graphically in real time.<\/jats:p>","DOI":"10.1017\/s1471068421000090","type":"journal-article","created":{"date-parts":[[2021,7,14]],"date-time":"2021-07-14T07:01:47Z","timestamp":1626246107000},"page":"229-253","update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":7,"title":["Operating Room (Re)Scheduling with Bed Management via ASP"],"prefix":"10.1017","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5617-5286","authenticated-orcid":false,"given":"CARMINE","family":"DODARO","sequence":"first","affiliation":[]},{"given":"GIUSEPPE","family":"GALAT\u00c0","sequence":"additional","affiliation":[]},{"given":"MUHAMMAD","family":"KAMRAN KHAN","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9034-2527","authenticated-orcid":false,"given":"MARCO","family":"MARATEA","sequence":"additional","affiliation":[]},{"given":"IVAN","family":"PORRO","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2021,7,14]]},"reference":[{"key":"S1471068421000090_ref27","doi-asserted-by":"crossref","unstructured":"Gebser, M. , Kaufmann, B. and Schaub, T. 2012. Conflict-driven answer set solving: From theory to practice. Artificial Intelligence 187, 52\u201389.","DOI":"10.1016\/j.artint.2012.04.001"},{"key":"S1471068421000090_ref3","doi-asserted-by":"crossref","unstructured":"Alviano, M. , Dodaro, C. and Maratea, M. 2017. An advanced answer set programming encoding for nurse scheduling. In Advances in Artificial Intelligence - Proceedings of the 16th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2017), F. Esposito, R. Basili, S. Ferilli, and F. A. Lisi, Eds. Lecture Notes in Computer Science, vol. 10640. Springer, 468\u2013482.","DOI":"10.1007\/978-3-319-70169-1_35"},{"key":"S1471068421000090_ref40","doi-asserted-by":"crossref","unstructured":"Zhang, J. , Dridi, M. and Moudni, A. E. 2017. A stochastic shortest-path MDP model with dead ends for operating rooms planning. In Proceedings of the 23rd International Conference on Automation and Computing (ICAC 2017). IEEE, 1\u20136.","DOI":"10.23919\/IConAC.2017.8081974"},{"key":"S1471068421000090_ref19","doi-asserted-by":"crossref","unstructured":"Dodaro, C. , Galat\u00e0, G. , Maratea, M. and Porro, I. 2018. Operating room scheduling via answer set programming. In Advances in Artificial Intelligence - Proceedings of the 17th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2018), C. Ghidini, B. Magnini, A. Passerini, and P. Traverso, Eds. Lecture Notes in Computer Science, vol. 11298. Springer, 445\u2013459.","DOI":"10.1007\/978-3-030-03840-3_33"},{"key":"S1471068421000090_ref1","doi-asserted-by":"crossref","unstructured":"Abedini, A. , Ye, H. and Li, W. 2016. Operating room planning under surgery type and priority constraints. Procedia Manufacturing 5, 15\u201325.","DOI":"10.1016\/j.promfg.2016.08.005"},{"key":"S1471068421000090_ref33","doi-asserted-by":"crossref","unstructured":"Giunchiglia, E. , Maratea, M. and Tacchella, A. 2002. Dependent and independent variables in propositional satisfiability. In Proceedings of the European Conference on Logics in Artificial Intelligence (JELIA 2002), S. Flesca, S. Greco, N. Leone, and G. Ianni, Eds. Lecture Notes in Computer Science, vol. 2424. Springer, 296\u2013307.","DOI":"10.1007\/3-540-45757-7_25"},{"key":"S1471068421000090_ref36","doi-asserted-by":"crossref","unstructured":"Molina-Pariente, J. M. , Hans, E. W. , Framinan, J. M. and Gomez-Cia, T. 2015. New heuristics for planning operating rooms. Computers & Industrial Engineering 90, 429\u2013443.","DOI":"10.1016\/j.cie.2015.10.002"},{"key":"S1471068421000090_ref8","doi-asserted-by":"crossref","unstructured":"Amendola, G. , Dodaro, C. , Leone, N. and Ricca, F. 2016. On the application of answer set programming to the conference paper assignment problem. In Advances in Artificial Intelligence - Proceedings of the 15th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2016), G. Adorni, S. Cagnoni, M. Gori, and M. Maratea, Eds. Lecture Notes in Computer Science, vol. 10037. Springer, 164\u2013178.","DOI":"10.1007\/978-3-319-49130-1_13"},{"key":"S1471068421000090_ref15","doi-asserted-by":"publisher","DOI":"10.1017\/S1471068419000450"},{"key":"S1471068421000090_ref2","doi-asserted-by":"crossref","unstructured":"Alviano, M. , Amendola, G. , Dodaro, C. , Leone, N. , Maratea, M. and Ricca, F. 2019. Evaluation of disjunctive programs in WASP. In Proceedings of the 15th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR 2019), M. Balduccini, Y. Lierler, and S. Woltran, Eds. Lecture Notes in Computer Science, vol. 11481. Springer, 241\u2013255.","DOI":"10.1007\/978-3-030-20528-7_18"},{"key":"S1471068421000090_ref24","first-page":"25","article-title":"Logic programs with propositional connectives and aggregates","volume":"4","author":"Ferraris","year":"2011","journal-title":"ACM Transactions on Computational Logic 12"},{"key":"S1471068421000090_ref21","doi-asserted-by":"crossref","unstructured":"Dodaro, C. and Maratea, M. 2017. Nurse scheduling via answer set programming. In Proceedings of the 14th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR 2017), M. Balduccini and T. Janhunen, Eds. Lecture Notes in Computer Science, vol. 10377. Springer, 301\u2013307.","DOI":"10.1007\/978-3-319-61660-5_27"},{"key":"S1471068421000090_ref37","doi-asserted-by":"publisher","DOI":"10.1023\/A:1018930122475"},{"key":"S1471068421000090_ref39","unstructured":"Rosa, E. D. , Giunchiglia, E. and Maratea, M. 2008. A new approach for solving satisfiability problems with qualitative preferences. In ECAI, M. Ghallab, C. D. Spyropoulos, N. Fakotakis, and N. M. Avouris, Eds. Frontiers in Artificial Intelligence and Applications, vol. 178. IOS Press, 510\u2013514."},{"key":"S1471068421000090_ref34","doi-asserted-by":"crossref","unstructured":"Giunchiglia, E. , Maratea, M. and Tacchella, A. 2003. (In)Effectiveness of look-ahead techniques in a modern SAT solver. In Proceedings of the 9th International Conference on Principles and Practice of Constraint Programming (CP 2003), F. Rossi, Ed. Lecture Notes in Computer Science, vol. 2833. Springer, 842\u2013846.","DOI":"10.1007\/978-3-540-45193-8_64"},{"key":"S1471068421000090_ref35","doi-asserted-by":"crossref","unstructured":"Landa, P. , Aringhieri, R. , Soriano, P. , T\u00e0nfani, E. and Testi, A. 2016. A hybrid optimization algorithm for surgeries scheduling. Operations Research for Health Care 8, 103\u2013114.","DOI":"10.1016\/j.orhc.2016.01.001"},{"key":"S1471068421000090_ref9","doi-asserted-by":"crossref","unstructured":"Aringhieri, R. , Landa, P. , Soriano, P. , T\u00e0nfani, E. and Testi, A. 2015. A two level metaheuristic for the operating room scheduling and assignment problem. Computers & Operations Research 54, 21\u201334.","DOI":"10.1016\/j.cor.2014.08.014"},{"key":"S1471068421000090_ref10","doi-asserted-by":"crossref","unstructured":"Aringhieri, R. , Landa, P. and T\u00e0nfani, E. 2015. Assigning surgery cases to operating rooms: A vns approach for leveling ward beds occupancies. In Proceedings of the 3rd International Conference on Variable Neighborhood Search (VNS 2014). Electronic Notes in Discrete Mathematics 47, 173\u2013180.","DOI":"10.1016\/j.endm.2014.11.023"},{"key":"S1471068421000090_ref30","doi-asserted-by":"publisher","DOI":"10.1017\/S1471068418000182"},{"key":"S1471068421000090_ref5","doi-asserted-by":"publisher","DOI":"10.1093\/logcom\/exv061"},{"key":"S1471068421000090_ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2010.04.002"},{"key":"S1471068421000090_ref16","unstructured":"Calimeri, F. , Faber, W. , Gebser, M. , Ianni, G. , Kaminski, R. , Krennwallner, T. , Leone, N. , Ricca, F. and Schaub, T. 2013. ASP-Core-2 Input Language Format. https:\/\/www.mat.unical.it\/aspcomp2013\/files\/ASP-CORE-2.03c.pdf"},{"key":"S1471068421000090_ref20","doi-asserted-by":"publisher","DOI":"10.3233\/IA-190020"},{"key":"S1471068421000090_ref14","doi-asserted-by":"publisher","DOI":"10.1109\/69.877512"},{"key":"S1471068421000090_ref18","doi-asserted-by":"crossref","unstructured":"Dodaro, C. , Galat\u00e0, G. , Khan, M. K. , Maratea, M. and Porro, I. 2019. An ASP-based solution for operating room scheduling with beds management. In Proceedings of the Third International Joint Conference on Rules and Reasoning (RuleML+RR 2019), P. Fodor, M. Montali, D. Calvanese, and D. Roman, Eds. Lecture Notes in Computer Science, vol. 11784. Springer, 67\u201381.","DOI":"10.1007\/978-3-030-31095-0_5"},{"key":"S1471068421000090_ref38","doi-asserted-by":"crossref","unstructured":"Ricca, F. , Grasso, G. , Alviano, M. , Manna, M. , Lio, V. , Iiritano, S. and Leone, N. 2012. Team-building with answer set programming in the Gioia-Tauro seaport. Theory and Practice of Logic Programming 12, 3, 361\u2013381.","DOI":"10.1017\/S147106841100007X"},{"key":"S1471068421000090_ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2043174.2043195"},{"key":"S1471068421000090_ref11","doi-asserted-by":"crossref","unstructured":"Balduccini, M. 2011. Industrial-size scheduling with ASP+CP. In Logic Programming and Nonmonotonic Reasoning - 11th International Conference, LPNMR 2011, Vancouver, Canada, May 16\u201319, 2011. Proceedings. Lecture Notes in Computer Science, vol. 6645. Springer, 284\u2013296.","DOI":"10.1007\/978-3-642-20895-9_33"},{"key":"S1471068421000090_ref12","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511543357"},{"key":"S1471068421000090_ref28","doi-asserted-by":"crossref","unstructured":"Gebser, M. , Maratea, M. and Ricca, F. 2017a. The design of the seventh answer set programming competition. In LPNMR, M. Balduccini and T. Janhunen, Eds. Lecture Notes in Computer Science, vol. 10377. Springer, 3\u20139.","DOI":"10.1007\/978-3-319-61660-5_1"},{"key":"S1471068421000090_ref4","first-page":"109","article-title":"Nurse (re)scheduling via answer set programming","volume":"2","author":"Alviano","year":"2018","journal-title":"Intelligenza Artificiale 12"},{"key":"S1471068421000090_ref29","doi-asserted-by":"crossref","unstructured":"Gebser, M. , Maratea, M. and Ricca, F. 2017b. The sixth answer set programming competition. Journal of Artificial Intelligence Research 60, 41\u201395.","DOI":"10.1613\/jair.5373"},{"key":"S1471068421000090_ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s13218-018-0548-6"},{"key":"S1471068421000090_ref31","unstructured":"Gelfond, M. and Lifschitz, V. 1988. The stable model semantics for logic programming. In Proceedings of the Fifth International Conference and Symposium (ICLP\/SLP 1988) (2 Volumes). MIT Press, 1070\u20131080."},{"key":"S1471068421000090_ref25","doi-asserted-by":"publisher","DOI":"10.1017\/S1471068415000150"},{"key":"S1471068421000090_ref6","doi-asserted-by":"publisher","DOI":"10.1017\/S1471068415000228"},{"key":"S1471068421000090_ref26","unstructured":"Gebser, M. , Kaminski, R. , Kaufmann, B. , Ostrowski, M. , Schaub, T. and Wanko, P. 2016. Theory solving made easy with clingo 5. In Proceedings of ICLP (Technical Communications), M. Carro, A. King, N. Saeedloei, and M. D. Vos, Eds. OASICS, vol. 52. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2:1\u20132:15."},{"key":"S1471068421000090_ref7","unstructured":"Amendola, G. 2018. Preliminary results on modeling interdependent scheduling games via answer set programming. In RiCeRcA@AI*IA. CEUR Workshop Proceedings, vol. 2272. CEUR-WS.org."},{"key":"S1471068421000090_ref32","doi-asserted-by":"crossref","unstructured":"Gelfond, M. and Lifschitz, V. 1991. Classical negation in logic programs and disjunctive databases. New Generation Computing 9, 3\/4, 365\u2013386.","DOI":"10.1007\/BF03037169"},{"key":"S1471068421000090_ref17","doi-asserted-by":"crossref","unstructured":"Calimeri, F. , Gebser, M. , Maratea, M. and Ricca, F. 2016. Design and results of the Fifth Answer Set Programming Competition. Artificial Intelligence 231, 151\u2013181.","DOI":"10.1016\/j.artint.2015.09.008"}],"container-title":["Theory and Practice of Logic Programming"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S1471068421000090","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,4]],"date-time":"2022-04-04T04:16:19Z","timestamp":1649045779000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S1471068421000090\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,14]]},"references-count":40,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2022,3]]}},"alternative-id":["S1471068421000090"],"URL":"https:\/\/doi.org\/10.1017\/s1471068421000090","relation":{},"ISSN":["1471-0684","1475-3081"],"issn-type":[{"type":"print","value":"1471-0684"},{"type":"electronic","value":"1475-3081"}],"subject":[],"published":{"date-parts":[[2021,7,14]]},"assertion":[{"value":"\u00a9 The Author(s), 2021. Published by Cambridge University Press","name":"copyright","label":"Copyright","group":{"name":"copyright_and_licensing","label":"Copyright and Licensing"}}]}}