Support optimal scheduling with weighted random forest for operation resources

Operation-related resources are lots of manpower and material with the characteristics of high cost and high income in hospitals,and scheduling optimization is a very important research issue in medical service.In this paper,to cope with the actualities of operation resources scheduling,such as poor planning,lack of standardized scheduling rules,chaotic use of the operating rooms,and many human interference factors,we propose a systematic approach to optimize scheduling problems based on multiple characteristics of operating resources.We frst design a framework that includes the composite dispatching rules(CDR),optimization ideology,and feedback mechanism,in which the CDR integrates fexible operating time,hold-up time of medical facilities,available time of medical staf,and multiple constraints.The optimization ideology is carried out through a learning model based on the weighted random forest(WRF)algorithm.The feedback mechanism enables the approach to realize closed-loop optimizations adaptively.Finally,the superiority of the systematic scheduling approach(SSA)is analyzed through numerical experiments on a simulation platform.Results of the simulation experiments show that the proposed scheduling method can improve performances signifcantly,especially in the waiting time of patients.

Evaluation System and Correlation Analysis for Determining the Performance of a Semiconductor Manufacturing System

Numerous performance indicators exist for semiconductor manufacturing systems.Several studies have been conducted regarding the performance optimization of semiconductor manufacturing systems.However,because of the complex manufacturing processes,potential complementary or inhibitory correlations may exist among performance indicators,which are difficult to demonstrate specifically.To analyze the correlation between the performance indicators,this study proposes a performance evaluation system based on the mathematical significance of each performance indicator to design statistical schemes.Several samples can be obtained by conducting simulation experiments through the performance evaluation system.The Pearson correlation coefficient method and canonical correlation analysis are used on the received samples to analyze linear correlations between the performance indicators.Through the investigation,we found that linear and other complex correlations exist between the performance indicators.This finding can contribute to our future studies regarding performance optimization for the scheduling problems of semiconductor manufacturing.