Bingrui Gao
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Bingrui Gao has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Bingyin Lei
School of Economics and Management, Beijing Information Science and Technology University, Beijing, China
1 shared publication - Kaiye Gao
School of Economics and Management, Beijing Forestry University, Beijing, China
1 shared publication - Li Guo
School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China
1 shared publication - Li Yang
School of Reliability and Systems Engineering, Beihang University, Beijing, China
1 shared publication - Qihang Li
School of Mathematics and Information Science, Zhongyuan University of Technology, Zhengzhou 450007, China
1 shared publication - Shu Fang
School of Economics and Management, Beijing University of Technology, Beijing 100124, China
1 shared publication
Latest Publications
- Open Access
A Review of Optimization Studies for System Appointment Scheduling
In the face of an increasingly high-demand environment for outpatients, achieving a balance between allocation of limited medical resources and patient satisfaction has considerable social and economic benefits. Therefore, appointment scheduling (AS) system operation is used in clinics and hospitals, and its operation optimization research is of great significance. This study reviews the research progress on appointment scheduling system optimization. Firstly, we classify and conclude the existing appointment scheduling system structures and decision-making frameworks. Subsequently, we summarize the system reliability optimization framework from three aspects: appointment scheduling system optimization objectives, decision variables and constraints. Following that, we methodically review the most applied system optimization algorithms in different appointment scheduling systems. Lastly, a literature bibliometric analysis is provided. During our review of the literature, we observe that (1) optimization methods in ASs predominantly involve the application of genetic algorithms and simulation optimization algorithms; (2) neural networks and deep learning methods are core technologies in health management optimization; (3) a bibliometric analysis reveals a heightened interest in the optimization technology of ASs within China compared to other nations; and (4) further advancements are essential in the comprehensive optimization of the system, exploration of practical usage scenarios, and the application of advanced simulation and modeling techniques in this research.
Open AccessA Review of Optimization Studies for System Appointment Scheduling
In the face of an increasingly high-demand environment for outpatients, achieving a balance between allocation of limited medical resources and patient satisfaction has considerable social and economic benefits. Therefore, appointment scheduling (AS) system operation is used in clinics and hospitals, and its operation optimization research is of great significance. This study reviews the research progress on appointment scheduling system optimization. Firstly, we classify and conclude the existing appointment scheduling system structures and decision-making frameworks. Subsequently, we summarize the system reliability optimization framework from three aspects: appointment scheduling system optimization objectives, decision variables and constraints. Following that, we methodically review the most applied system optimization algorithms in different appointment scheduling systems. Lastly, a literature bibliometric analysis is provided. During our review of the literature, we observe that (1) optimization methods in ASs predominantly involve the application of genetic algorithms and simulation optimization algorithms; (2) neural networks and deep learning methods are core technologies in health management optimization; (3) a bibliometric analysis reveals a heightened interest in the optimization technology of ASs within China compared to other nations; and (4) further advancements are essential in the comprehensive optimization of the system, exploration of practical usage scenarios, and the application of advanced simulation and modeling techniques in this research.