Research on Artificial Seat Scheduling Algorithm Based on Genetic Algorithm

This article analyzes the call data of a certain call center, categorizes and summarizes the conversation volume, and fits the data. The analysis results show that with the promotion and application of artificial intelligence, AI customer service and human agents have achieved a natural division of labor in business. At the same time, the demand for human agents is also more precise and demanding. On the premise of fully analyzing the characteristics of human seat traffic data, based on the actual traffic data of the company, the required number of human seats was simulated and calculated. With the goal of balancing the workload of human seats, a mathematical model was established with the minimum square difference between the per capita workload of the scheduling plan and the standard workload. In response to this model, the 4-week scheduling results of seat personnel were used as chromosomes, and based on the basic genetic algorithm, the elite strategy and cross mutation operator in natural selection were improved to accelerate algorithm convergence and achieve the final optimal scheduling plan.