Research On Customer Appointment And Sequence Scheduling Of Health Examination Organization Based On Meta-heuristic Algorithm

With the improvement of the national economic level and the enhancement of health awareness,more and more people take regular health examinations.Most domestic health examination institutions are still in the traditional management mode and their work efficiency is low,which has caused the queuing problem of health examination institutions to become more and more serious,which affects customer satisfaction.Customer scheduling is one of the effective means to reduce customer waiting.The customer scheduling of the health examination service mainly includes the appointment scheduling and the sequential scheduling optimization of health examination items.Therefore,this paper focuses on the health examination customers,from appointment scheduling and health examination item sequential scheduling,to reduce the customer’s waiting time.The main research content includes the following three aspects.First,for the scheduling problem of the sequence of customer health examination items,assuming that the service duration is fixed.A multi-objective mixed integer programming model is established,and a hybrid genetic algorithm is designed to solve it.Numerical experiments verify the effectiveness of the proposed solution by comparing hybrid genetic algorithm,basic genetic algorithm and heuristic scheduling strategy.Secondly,for the sequential scheduling problem of customer health examination items,assuming that the service duration is random.This paper constructs a simulation optimization algorithm,combined with the sequence optimization idea,using hybrid genetic algorithm as the evolution strategy,and through the optimal calculation allocation method,forming a global simulation resource and adaptive optimization allocation mechanism.Numerical experiments verify the effectiveness of the designed simulation optimization algorithm by comparing with different heuristic scheduling rules.Finally,for the customer appointment scheduling problem,two cases of fixed service duration and random service duration are considered.Multi-person time slot scheduling rule is used to optimize the number of customers in each scheduling batch,and at the same time the sequence of health examination items for each customers is arranged.For the fixed service duration,this paper proposes an improved multi-population genetic algorithm based on cross-affinity evaluation.The results of the multi-population genetic algorithm are compared with the results of the hybrid genetic algorithm to verify the effectiveness of the algorithm.For the problem of random service duration,a two-stage simulation optimization framework is established,and the multi-population genetic algorithm is used as the iteration strategy.The results of the algorithm are compared with the results of two-stage simulation optimization using hybrid genetic algorithm as the iterative strategy to verify the effectiveness of the algorithm.The results of this study can provide managers of health examination institutions and similar service institutions with effective customer scheduling method to reduce customer wait time,improve the level of resource utilization and increase the competitiveness of an institution.It can also assist the managers of health examination institutions to make decisions to increase the input of key project equipment or personnel,and balance the service capabilities of congested and non-congested projects,thereby improving the overall service level of the health examination system.