关键词: 层流手术调度, 可重入, 多目标, 绿色调度, NSGA-II算法

Abstract: With the prevalence of laminar flow operating rooms in hospitals, scheduling for such operating rooms hasbecome a critical concern in hospital operations management. Compared to conventional operatingrooms, laminar flow operating rooms consume a significant amount of energy while providing a cleaner, more comfortable, and safer surgical environment for patients. Faced with the challenge of high energy consumption in laminar flow operating rooms, hospitals often implement technological, managerial, and behavioral energy-saving measures. The generation of energy consumption is primarily driven by the demand for medical activities. As a pivotal department in hospitals, operating rooms involve extensive medical activities and costs. Therefore, from the perspective of energy-efficient management, this paper proposes research on the green scheduling problem of laminar flow surgery centers, focusing on optimizing scheduling to assist hospitals in providing higher-quality surgical medical services to patients with reduced energy consumption and lower costs.
In the context of pursuing environmental sustainability andlow-carbon initiatives, this paper proposes research on thegreen scheduling of laminar flow surgery centers, considering the interests of multiple stakeholders, including patients, hospitals, and society. Firstly, we employ “perceived preoperative wait time” as a metric for patient satisfaction to improve the preoperative waiting process, and address the most frequent patient complaints. Secondly, we use “laminar flow operating center usage duration” as an indicator for hospital surgical system operations to offer patients services with fewer overtime hours, reduced costs, and increased efficiency. Finally, we take “carbonemissions” as a green indicator to reflect the hospital's green initiatives and social responsibility.
For the multi-objective laminar flow surgery green scheduling problem, this study develops a reentrant laminar flow surgery green scheduling model with objectives including patient preoperative waiting time, surgery center utilization time, and carbon emissions. A hybrid improved optimization algorithm (INSGAII-LS) is proposed for solving this problem. The algorithm introduces innovative cooperative search strategies, population initialization policies, variable-scale crossover and mutation strategies, as well as a depth-first search iteration strategy within local search, enhancing the search capability of the solution space. Additionally, considering the characteristics of the problem, a data-driven decoding strategy is designed and its effectiveness is verified. The study conducts numerical experiments and simulation tests at different scales, comparing the performance and stability of the proposed algorithm to other effective algorithms (IMSSA, IMOGWO, NSGA-II). The simulation results indicate that the key factor determining the duration of surgical center utilization duration is patient prioritization. However, reducing the duration of the laminar flow operating center does not directly lead to a decrease in carbon emissions. It is essential to consider the cumulative carbon emissions generated by the operating room. Consequently, scheduling operating rooms is crucial in surgical planning. The research outcomes can provide valuable insights and decision references for the multi-objective optimization in green scheduling of the laminar flow operating center.
It should be noted that the proposed decoding strategy in this paper relies on reliable data prediction. In the future, the author'steam will conduct research focused on predicting service duration around the laminar flow operating center.This will involve exploring reentrant laminar flow green scheduling under the uncertainty of surgicalduration and studying distributed surgical green scheduling within the context of internet healthcare.
These efforts aim to provide new theoretical foundations, methodological insights, and decision references for the green operation of laminar flow operating centers.

Key words: laminar flow surgical scheduling, reentrant, multi-objective, green scheduling, NSGA-II algorithm