Abstract: The dynamic programming method to solve the cascade pumping station scheduling problem is very classic, but there is a “dimensional disaster” problem in the calculation, GPU parallel computing technology can accelerate the repetitive calculations and improve the computational performance of the algorithm. This paper analyzes the dynamic planning method of cascade pumping station scheduling problems, uses CUDA (Unified Computing Device Architecture) to improve the scheduling algorithm, and gives the improved dynamic programming algorithm, and compares the time-consuming of the scheduling algorithm calculation under different computing scales. The experimental results show that the cascade pumping station scheduling algorithm based on CUDA improved dynamic programming method can reduce the calculation dimension. When the calculation scale is large, the acceleration effect is better.

Key words: cascade pumping station scheduling, dynamic programming, parallel computing, CUDA