Research On Dispatching Optimization Of Internet Medical Call Center

With the development of technology,the Internet is quietly changing people’s lifestyles,and big data applications are entering people’s lives.Call centers have become a common way for Internet medical services to provide services to customers.At the same time,the high-quality services of call centers are an important way to increase the competitiveness of enterprises.Company A’s call center scheduling is an important part of the company’s operating plan,and the labor cost of the call center accounts for about 70% of the total operating costs.However,with the expansion of call center scale and business segmentation,the scheduling problem is becoming more and more complicated.In order to improve the work efficiency of the call center,minimize operating costs,and realize the reasonable allocation of human resources of company A,it is the operation and management of company A.A major issue.Therefore,this article will establish a scheduling problem model that meets the needs of employees and complies with labor laws and regulations based on the relevant theories of big data applications in statistics.The employee scheduling problem in call centers is a more difficult NP problem than the TSP problem.The employee scheduling is a combinatorial optimization problem.Using integer programming to solve the problem is computationally difficult,while the heuristic algorithm has flexible calculations,simple and intuitive algorithms,and easy to modify And can give a better solution within an acceptable time.This article takes an Internet medical company as an example to study the scheduling problem in the operation and management of the call center.The main research contents and innovations of this paper are as follows:First,because the system solves the scheduling problem,the consultation volume needs to be forecasted.The consultation volume forecast is based on historical data to explore and analyze,find out its changing rules,and combine operating activity information to predict the data for the next week.In order to rationally arrange resources and improve efficiency,this article first gives a detailed description of common call center consultation volume forecasting methods,including exponential smoothing and regression analysis.Through different analyses,the year,month,week,day,and forecast the consultation volume during the time period.Second,the scheduling problem is an NP complete problem,a typical combinatorial optimization and uncertain scheduling problem.In this paper,the branch and bound method based on integer programming and the simulated annealing algorithm,from the perspective of the practicability and feasibility of the company’s call center work,combined with the results of the questionnaire,systematically explain the scheduling problem,and minimize labor costs as the optimization goal,Establish an employee scheduling model with constraints.Third,introduce the branch and bound method and simulated annealing algorithm of integer programming.Combining the advantages and disadvantages of the two algorithms,design a hybrid optimization strategy of simulated annealing and branch and bound algorithms.Use matlab to solve the model.The experimental results show that the scheduling model satisfies labor regulations,company operating requirements and employee needs,and the quality of the solution of the hybrid optimization algorithm is better than that of a single branch and bound algorithm and heuristic algorithm.