Optimization Analysis of Dynamic Economic Environment Scheduling Problem Based on Differential Evolution Algorithm

Differential evolution algorithm is a common optimization algorithm with extensive applications in solving dynamic economic environment scheduling problems. The dynamic and uncertainty of economic activities make it difficult to achieve efficient resource scheduling and economic benefit maximization in the dynamic economic environment. In this paper, we study dynamic economic environment scheduling based on a differential evolution algorithm. First, the background and significance of dynamic economic environment scheduling are expounded. Then we analyze the key factors and optimization strategies of this method in the optimization process. Finally, the power generation cost results of DE algorithm are 2.4805,2.4653,2.4196 and 2.5016 (* 106$), which are the lowest cost compared with other algorithms. The experimental results show that the optimization method of dynamic economic environment scheduling problem based on differential evolution algorithm can solve the problem effectively, and has high optimization effect and application value. The method can not only ensure the economy, but also adapt to the change of dynamic environment, with high practicability and operability.