| With the improvement of people’s living standards,regular physical examination has become one of the main ways for people to judge their own health status and measure their immunity level.However,compared with the limited medical resources,the number of customers who need medical examinations is extremely large.How to plan the orderly scheduling of customers going to the medical examination center has become a particularly important issue.Considering the fact that only a single physical examination item is checked among customers with physical examination demands,this dissertation will mainly carry out the scheduling optimization research of the single physical examination guide inspection system.This dissertation is based on the phenomenon of learning effect in scheduling in the operation process of medical staff in the guide inspection system of a single physical examination item.Using scheduling theory,the two proposed guide inspection system optimization indicators are:(a)reduce customer queuing time,(b)improve the operation efficiency of the overall system.In this dissertation,firstly,for the situation with the learning effect in the guide inspection system,the scheduling problem with the optimization goal of reducing the waiting time of customers in the queue is abstracted as a single-machine online scheduling study that minimizes the sum of the total completion time under the learning effect.After the lower bound of the scheduling problem is obtained,an online algorithm DSBPT is designed in combination with the lower bound of the problem.Using the "peeling onion" analysis method,the algorithm is the best possible and the competitive ratio is 2.Secondly,in the analysis of the scheduling problem whose optimization goal is to improve the operation efficiency of the entire medical examination system,we limit the learning effect mentioned above to the truncated learning effect,that is,the problem is abstracted as a single machine online scheduling study that minimizes the maximum completion time under the of truncated learning effect.After analyzing and obtaining the lower bound of the scheduling problem,an online algorithm DSOPT is proposed,and the algorithm is the best possible and the competitive ratio is 2-θ obtained by using the "peeling onion" analysis method.Thirdly,we abstract the customer information of the guide inspection system into an online scheduling example,for the online algorithms proposed for these two scheduling problems,the feasibility of the proposed two online algorithms is verified by the execution status of the two online algorithms and the final calculation results.Finally,we have made an overall summary of the research in this dissertation,and made corresponding expositions for future research directions.The two kinds of guide inspection system scheduling problems and corresponding online algorithms studied in this dissertation are conducive to enriching and deepening the relevant theoretical research on guiding inspection system scheduling optimization,and provide theoretical support for the medical system to make reasonable and feasible plans during system optimization,which provides a new research direction for follow-up research. |
