EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 412 (2023) E3S Web Conf., 412 (2023) 01074 References
Open Access

This article has an erratum: [https://doi.org/10.1051/e3sconf/202341201111]

Issue
E3S Web Conf.
Volume 412, 2023
International Conference on Innovation in Modern Applied Science, Environment, Energy and Earth Studies (ICIES’11 2023)
Article Number 01074
Number of page(s) 17
DOI https://doi.org/10.1051/e3sconf/202341201074
Published online 17 August 2023
  1. A. Macario, F. Dexter, R. D. Traub. Hospital profitability per hour of operating room time can vary among surgeons. Anesthesia & Analgesia, 93(3), 669-675 (2001). [CrossRef] [PubMed] [Google Scholar]
  2. M. Revel, G. Nicolas, C. Bara, M. O. Moreau, D. Nicolle, M. Duret. Synthèse des travaux du groupe sur l’implantation et l’organisation des plateaux techniques. Ministère de la santé, de la famille, et des personnes handicapées, 35p. (2003). [Google Scholar]
  3. M. Lamiri, J. Dreo, X. Xie. Operating room planning with random surgery times. In 2007 IEEE International Conference on Automation Science and Engineering (pp. 521-526). (2007, September). [Google Scholar]
  4. A. Testi, E. Tanfani, G. Torre. A three-phase approach for operating theatre schedules. Health care management science, 10(2), 163-172. (2007). [CrossRef] [PubMed] [Google Scholar]
  5. H. Fei, N. Meskens, C. Chu. A planning and scheduling problem for an operating theatre using an open scheduling strategy. Computers & Industrial Engineering, 58(2), 221-230. (2010). [CrossRef] [Google Scholar]
  6. Y. Liu, C. Chu, K. Wang. A new heuristic algorithm for the operating room scheduling problem. Computers & Industrial Engineering, 61(3), 865-871. (2011). [CrossRef] [Google Scholar]
  7. F. Bonvoisin, Evaluation de la performance des blocs opératoires: du modèle aux indicateurs (Doctoral dissertation, Université de Valenciennes et du Hainaut-Cambresis). (2011). [Google Scholar]
  8. S. P. Devi, K. S. Rao, S. S. Sangeetha. Prediction of surgery times and scheduling of operation theaters in optholmology department. Journal of medical systems, 36(2), 415-430. (2012). [CrossRef] [PubMed] [Google Scholar]
  9. B. Addis, G. Carello, A. Grosso, E. Tànfani. Operating room scheduling and rescheduling: a rolling horizon approach. Flexible Services and Manufacturing Journal, 28(1), 206-232. (2016). [CrossRef] [Google Scholar]
  10. M. E. Bruni, P. Beraldi, D. Conforti. A stochastic programming approach for operating theatre scheduling under uncertainty. IMA Journal of Management Mathematics, 26(1), 99-119. (2015). [CrossRef] [Google Scholar]
  11. P. Cappanera, F. Visintin, C. Banditori. Addressing conflicting stakeholders’ priorities in surgical scheduling by goal programming. Flexible Services and Manufacturing Journal, 30(1), 252-271. (2018). [CrossRef] [Google Scholar]
  12. E. Hans, G. Wullink, M. Van Houdenhoven, G. Kazemier. Robust surgery loading. European Journal of Operational Research, 185(3), 1038-1050. (2008). [CrossRef] [Google Scholar]
  13. B. T. Denton, A. J. Miller, H. J. Balasubramanian, T. R. Huschka. Optimal allocation of surgery blocks to operating rooms under uncertainty. Operations research, 58(4-part-1), 802-816. (2010). [CrossRef] [Google Scholar]
  14. D. Min, Y. Yih. Scheduling elective surgery under uncertainty and downstream capacity constraints. European Journal of Operational Research, 206(3), 642-652. (2010). [CrossRef] [Google Scholar]
  15. S. Rachuba, B. Werners. A robust approach for scheduling in hospitals using multiple objectives. Journal of the Operational Research Society, 65(4), 546-556. (2014). [CrossRef] [Google Scholar]
  16. Y. Wang, J. Tang, R. Y. Fung. A column-generation-based heuristic algorithm for solving operating theater planning problem under stochastic demand and surgery cancellation risk. International Journal of Production Economics, 158, 28-36. (2014). [CrossRef] [Google Scholar]
  17. P. Landa, R. Aringhieri, P. Soriano, E. Tànfani, A. Testi. A hybrid optimization algorithm for surgeries scheduling. Operations Research for Health Care, 8, 103-114. (2016). [CrossRef] [Google Scholar]
  18. I. Marques, M. E. Captivo, & M. Vaz Pato. An integer programming approach to elective surgery scheduling. OR spectrum, 34(2), 407-427. (2012). [CrossRef] [Google Scholar]
  19. D. Conforti, F. Guerriero, R. Guido. A multi-objective block scheduling model for the management of surgical operating rooms: New solution approaches via genetic algorithms. In 2010 IEEE workshop on health care management (WHCM) (pp. 1-5). IEEE. (2010, February). [Google Scholar]
  20. I. Marques, M. E. Captivo, M. V. Pato. Scheduling elective surgeries in a Portuguese hospital using a genetic heuristic. Operations Research for Health Care, 3(2), 59-72. (2014). [CrossRef] [Google Scholar]
  21. E. Marcon, K. Said, & S. Gerard. Minimization of the risk of no realization for the planning of the surgical interventions into the operating theatre. In ETFA 2001. 8th International Conference on Emerging Technologies and Factory Automation. Proceedings (Cat. No. 01TH8597) (pp. 675680). IEEE. (2001, October). [Google Scholar]
  22. E. Marcon, S. Kharraja G. Simonnet. The operating theatre planning by the follow-up of the risk of no realization. International Journal of Production Economics, 85(1), 83-90. (2003). [CrossRef] [Google Scholar]
  23. L. Dekhici, & B. Khaled. Operating theatre scheduling under constraints. Journal of Applied Sciences, 14(10), 1380-1388. (2010). [CrossRef] [Google Scholar]
  24. G. X. Huang, W. Xiang, C. Li, Q. Zheng, S. Zhou, B. Q. Shen, & S. F. Chen. Surgical scheduling based on hybrid flow-shop scheduling. In Applied Mechanics and Materials (Vol. 201, pp. 10041007). Trans Tech Publications Ltd. (2012). [Google Scholar]
  25. W. Yu, M. Yunhui, Z. Huabo, T. Jiafu. A particle swarm optimization algorithm on the surgery scheduling problem with downstream process. In 2013 25th Chinese Control and Decision Conference (CCDC) (pp. 850-855). IEEE. (2013, May). [Google Scholar]
  26. S. Lee, Y. Yih. Reducing patient-flow delays in surgical suites through determining start-times of surgical cases. European Journal of Operational Research, 238(2), 620-629. (2014). [CrossRef] [Google Scholar]
  27. H. W. Kuhn. The hungarian method for the assignment problem. In 50 Years of Integer Programming 1958-2008. Springer, 6, 29-47. (2010). [CrossRef] [Google Scholar]
  28. A. Jebali, A. B. H. Alouane, P. Ladet. Operating rooms scheduling. International Journal of Production Economics, 99(1-2), 52-62. (2006). [CrossRef] [Google Scholar]
  29. S. Kharraja. Outils d’aide à la planification et l’ordonnancement des plateaux médicotechniques (Doctoral dissertation, Saint-Etienne). (2003). [Google Scholar]
  30. S. Chaabane, A. Guinet, L. Trilling. Pilotage conjoint de ressources hospitalières humaines et matérielles: un problème d’ordonnancement avec cycles. In Conférence GISEH (pp. 9-11). (2004, September). [Google Scholar]
  31. V. Perdomo, V. Augusto, X. Xie, Operating theatre scheduling using lagrangian relaxation. In 2006 International Conference on Service Systems and Service Management (Vol. 2, pp. 1234-1239). IEEE. (2006, October). [Google Scholar]
  32. V. Augusto, X. Xie, V. Perdomo. Operating theatre scheduling with patient recovery in both operating rooms and recovery beds. Computers & Industrial Engineering, 58(2), 231-238. (2010). [CrossRef] [Google Scholar]
  33. S. C. Kim, I. Horowitz, K. K. Young, T. A. Buckley. Analysis of capacity management of the intensive care unit in a hospital. European Journal of Operational Research, 115(1), 36-46. (1999). [CrossRef] [Google Scholar]
  34. K. Seung-Chul, H. Ira. Flexible bed allocation and performance in the intensive care unit. Journal of Operations Management, 18(4), 427-443. (2000). [CrossRef] [Google Scholar]
  35. S. C. Kim, I. Horowitz. Scheduling hospital services: the efficacy of elective-surgery quotas. Omega, 30(5), 335-346. (2002). [CrossRef] [Google Scholar]
  36. S. Kharraja, P. Albert, S. Chaabane. Block scheduling: Toward a master surgical schedule. In 2006 International Conference on Service Systems and Service Management (Vol. 1, pp. 429-435). IEEE. (2006, October). [Google Scholar]
  37. N. Smolski, E. Marcon, S. Chaabane, B. Luquet, J. Viale. Impact des stratégies de brancardage sur l’occupation de la SSPI: étude par simulation. 44ème Congrès national d’Anesthésie et de Réanimation, 19-22. (2002). [Google Scholar]
  38. V. N. Hsu, R. De Matta, C. Y. Lee. Scheduling patients in an ambulatory surgical center. Naval Research Logistics (NRL), 50(3), 218-238. (2003). [CrossRef] [Google Scholar]
  39. B. Vijayakumar, P. J. Parikh, R. Scott, A. Barnes, J. Gallimore. A dual bin-packing approach to scheduling surgical cases at a publicly-funded hospital. European Journal of Operational Research, 224(3), 583-591. (2013). [CrossRef] [Google Scholar]
  40. D. N. Pham, A. Klinkert. Surgical case scheduling as a generalized job shop scheduling problem. European Journal of Operational Research, 185(3), 1011-1025. (2008). [CrossRef] [Google Scholar]
  41. B. Roland, C. Di Martinelly, F. Riane. Operating theatre optimization: A resource-constrained based solving approach. In 2006 International conference on service systems and service management (Vol. 1, pp. 443-448). IEEE. (2006, October). [Google Scholar]
  42. J. Pensi. Résolution conjointe des problèmes de planification des opérations chirurgicales et des opérations de maintenance: application au cas des hôpitaux camerounais. Doctoral dissertation, Université Clermont Auvergne. (2017). [Google Scholar]
  43. B. Fleischmann. The discrete lot-sizing and scheduling problem. European Journal of Operational Research, 44(3), 337-348. (1990). [CrossRef] [Google Scholar]
  44. C. Wolosewicz, S. Dauzère-Pérès, R. Aggoune. A new approach for solving integrated planning and scheduling problem. IFAC Proceedings Volumes, 39(3), 191-196. (2006). [Google Scholar]
  45. J. M. Molina-Pariente, V. Fernandez-Viagas, J. M. Framinan. Integrated operating room planning and scheduling problem with assistant surgeon dependent surgery durations. Computers & Industrial Engineering, 82, 8-20. (2015). [CrossRef] [Google Scholar]
  46. B. Roland, C. Di Martinelly, F. Riane, Y. Pochet. Scheduling an operating theatre under human resource constraints. Computers & Industrial Engineering, 58(2), 212-220. (2010). [CrossRef] [Google Scholar]
  47. S. Kharraja, S. Hammami, R. Abbou. Plan Directeur d’Allocation des plages horaires: approche globale. Gestion et Ingénierie des Systèmes Hospitaliers, GISEH’04. (2004). [Google Scholar]
  48. H. Fei, A. Artiba, N. Meskens, & C. Chu. Planification des interventions sur une semaine dans un bloc opératoire. (2005). [Google Scholar]
  49. S. Hammami, P. Ladet, B. H. A. Atidel, A. Ruiz. Une programmation opératoire robuste. Logistique & Management, 15(1), 95-111. (2007). [CrossRef] [Google Scholar]
  50. S. Chaabane, N. Meskens, A. Guinet, M. Laurent. Comparaison des performances des politiques de programmation opératoire. Logistique Management, 15(1), 17-26. (2007). [CrossRef] [Google Scholar]
  51. H. Fei, C. Chu, N. Meskens, A. Artiba. Solving surgical cases assignment problem by a branchand-price approach. International journal of production economics, 112(1), 96-108. (2008). [CrossRef] [Google Scholar]
  52. S. Chaabane, N. Meskens, A. Guinet, M. Laurent. Comparison of two methods of operating theatre planning: application in Belgian hospital. Journal of Systems Science and Systems Engineering, 17, 171-186. (2008). [CrossRef] [Google Scholar]
  53. J. H. Iser, B. T. Denton, R. E. King. Heuristics for balancing operating room and post-anesthesia resources under uncertainty. In 2008 Winter Simulation Conference (pp. 1601-1608). IEEE. (2008, December). [Google Scholar]
  54. S. Rodier. An attempt to unify and solve the questions of modeling and optimization within the hospital systems. Application to the New Estaing Hospital. Computer Science, Blaise Pascal University-Clermont-Ferrand II, France. (2010). [Google Scholar]
  55. S. A. N. A. Aniba, A. I. D. A. Jebali. Approches stochastiques pour la planification des interventions au bloc opératoire. 9è Congrès International de Génie Industriel (CIGI’2011). (2011). [Google Scholar]
  56. A. Agnetis, A. Coppi, M. Corsini, G. Dellino, C. Meloni, M. Pranzo. Long term evaluation of operating theater planning policies. Operations Research for Health Care, 1(4), 95-104. (2012). [CrossRef] [Google Scholar]
  57. A. Bouguerra, C. Sauvey, N. Sauer. Mathematical model for maximizing operating rooms utilization. IFAC-PapersOnLine, 48(3), 118-123. (2015). [CrossRef] [Google Scholar]
  58. J. Razmi, M. S. Yousefi, M. Barati. A stochastic model for operating room unique equipment planning under uncertainty. IFAC-PapersOnLine, 48(3), 1796-1801. (2015). [CrossRef] [Google Scholar]
  59. A. Chraibi. Outils d’aide à la décision pour la conception des blocs opératoires (Doctoral dissertation, Université Jean Monnet-Saint-Etienne). (2015). [Google Scholar]
  60. A. Duenas, C. D. Martinelly, G. Yazgı Tütüncü, J. Aguado. A multi-objective hospital operating room planning and scheduling problem using compromise programming. In Mexican International Conference on Artificial Intelligence (pp. 379-390). Springer, Cham. (2016, October). [Google Scholar]
  61. A. Augustin. Ordonnancement de bloc opératoire avec intégration des soins intensifs. Ecole Polytechnique, Montreal (Canada). (2017). [Google Scholar]
  62. L. W. Santoso, A. Sudiarso, N. A. Masruroh, M. K. Herliansyah. Cluster analysis to determine the priority of operating room scheduling. In AIP Conference Proceedings (Vol. 1977, No. 1, p. 020058). AIP Publishing LLC. (2018, June). [CrossRef] [Google Scholar]
  63. Ş. Gür, T. Eren, H. M. Alakaş. Surgical operation scheduling with goal programming and constraint programming: A case study. Mathematics, 7(3), 251. (2019). [CrossRef] [Google Scholar]
  64. B. B. Saleh. Approche Intelligence Artificielle Distribuée pour une planification réactive et une aide à la conduite du processus de blocs opératoires hospitaliers (Doctoral dissertation, Université Bourgogne Franche-Comté; Université Libanaise). (2019). [Google Scholar]
  65. V. Dorval. Planification des opérations chirurgicales sous contrainte de capacité. (2020). [Google Scholar]
  66. C. Arezki, J. P. Boufflet, L. Mezouari, A. Moukrim. Planification d’interventions chirurgicales: heuristiques de construction et d’amélioration. In 21e congrès annuel de la Société Française de Recherche Opérationnelle et d’Aide à la Décision (ROADEF 2020). (2020, February). [Google Scholar]
  67. Barakat, Y. et al (2021). What contributions of Artificial Intelligence in Innovation?. E3S Web of Conferences, 2021, 234, 00105 [CrossRef] [EDP Sciences] [Google Scholar]
  68. Y. Xiao, R. Yoogalingam. A simulation optimization approach for planning and scheduling in operating rooms for elective and urgent surgeries. Operations Research for Health Care, 35, 100366. (2022). [CrossRef] [Google Scholar]
  69. R. Bargetto, T. Garaix, X. Xie. A branch-and-price-and-cut algorithm for operating room scheduling under human resource constraints. Computers & Operations Research, 106136. (2023). [CrossRef] [Google Scholar]
  70. B. Cardoen, E. Demeulemeester, J. Beliën. Operating room planning and scheduling: A literature review. European journal of operational research, 201(3), 921-932. (2010). [CrossRef] [Google Scholar]
  71. İ. Ayçam, & A. Yazici. Evaluation of operating room units within the context of green design criteria. Gazi University Journal of Science, 30(1), 1-15. (2017). [Google Scholar]
  72. C. A. Balaras, E. Dascalaki, & A. Gaglia. HVAC and indoor thermal conditions in hospital operating rooms. Energy and Buildings, 39(4), 454-470. (2007). [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.