Multi-resource constrained elective surgical scheduling with Nash equilibrium toward smart hospitals
Abstract This paper focuses on the elective surgical scheduling problem with multi-resource constraints, including material resources, such as operating rooms (ORs) and non-operating room (NOR) beds, and human resources (i.e., surgeons, anesthesiologists, and nurses). The objective of multi-resource...
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-87867-y |
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| author | Jun Xue Zhi Li Shuangli Zhang |
| author_facet | Jun Xue Zhi Li Shuangli Zhang |
| author_sort | Jun Xue |
| collection | DOAJ |
| description | Abstract This paper focuses on the elective surgical scheduling problem with multi-resource constraints, including material resources, such as operating rooms (ORs) and non-operating room (NOR) beds, and human resources (i.e., surgeons, anesthesiologists, and nurses). The objective of multi-resource constrained elective surgical scheduling (MESS) is to simultaneously minimize the average recovery completion time for all patients, the average overtime for medical staffs, and the total medical cost. This problem can be formulated as a mixed integer linear multi-objective optimization model, and the honey badger algorithm based on the Nash equilibrium (HBA-NE) is developed for the MESS. Experimental studies were carried out to test the performance of the proposed approach, and the performance of the proposed surgical scheduling scheme was validated. Finally, to narrow the gap between the optimal surgical scheduling solution and actual hospital operations, digital twin (DT) technology is adopted to build a physical-virtual hospital surgery simulation model. The experimental results show that by introducing a digital twin, the physical and virtual spaces of the smart hospital can be integrated to visually simulate and verify surgical processes. |
| format | Article |
| id | doaj-art-ba3386dc988e4e79b97038ae24d34d0c |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-ba3386dc988e4e79b97038ae24d34d0c2025-02-02T12:20:36ZengNature PortfolioScientific Reports2045-23222025-01-0115113010.1038/s41598-025-87867-yMulti-resource constrained elective surgical scheduling with Nash equilibrium toward smart hospitalsJun Xue0Zhi Li1Shuangli Zhang2Department of General Surgery, Hebei Provincial Key Laboratory of Systems Biology and Gene Regulation, The First Affiliated Hospital of Hebei North UniversitySchool of Economics and Management, Tiangong UniversitySchool of Economics and Management, Tiangong UniversityAbstract This paper focuses on the elective surgical scheduling problem with multi-resource constraints, including material resources, such as operating rooms (ORs) and non-operating room (NOR) beds, and human resources (i.e., surgeons, anesthesiologists, and nurses). The objective of multi-resource constrained elective surgical scheduling (MESS) is to simultaneously minimize the average recovery completion time for all patients, the average overtime for medical staffs, and the total medical cost. This problem can be formulated as a mixed integer linear multi-objective optimization model, and the honey badger algorithm based on the Nash equilibrium (HBA-NE) is developed for the MESS. Experimental studies were carried out to test the performance of the proposed approach, and the performance of the proposed surgical scheduling scheme was validated. Finally, to narrow the gap between the optimal surgical scheduling solution and actual hospital operations, digital twin (DT) technology is adopted to build a physical-virtual hospital surgery simulation model. The experimental results show that by introducing a digital twin, the physical and virtual spaces of the smart hospital can be integrated to visually simulate and verify surgical processes.https://doi.org/10.1038/s41598-025-87867-yElective surgical schedulingSmart hospitalNash equilibriumHoney badger algorithm (HBA)Digital twin |
| spellingShingle | Jun Xue Zhi Li Shuangli Zhang Multi-resource constrained elective surgical scheduling with Nash equilibrium toward smart hospitals Scientific Reports Elective surgical scheduling Smart hospital Nash equilibrium Honey badger algorithm (HBA) Digital twin |
| title | Multi-resource constrained elective surgical scheduling with Nash equilibrium toward smart hospitals |
| title_full | Multi-resource constrained elective surgical scheduling with Nash equilibrium toward smart hospitals |
| title_fullStr | Multi-resource constrained elective surgical scheduling with Nash equilibrium toward smart hospitals |
| title_full_unstemmed | Multi-resource constrained elective surgical scheduling with Nash equilibrium toward smart hospitals |
| title_short | Multi-resource constrained elective surgical scheduling with Nash equilibrium toward smart hospitals |
| title_sort | multi resource constrained elective surgical scheduling with nash equilibrium toward smart hospitals |
| topic | Elective surgical scheduling Smart hospital Nash equilibrium Honey badger algorithm (HBA) Digital twin |
| url | https://doi.org/10.1038/s41598-025-87867-y |
| work_keys_str_mv | AT junxue multiresourceconstrainedelectivesurgicalschedulingwithnashequilibriumtowardsmarthospitals AT zhili multiresourceconstrainedelectivesurgicalschedulingwithnashequilibriumtowardsmarthospitals AT shuanglizhang multiresourceconstrainedelectivesurgicalschedulingwithnashequilibriumtowardsmarthospitals |