Earticle

Dynamic optimization scheduling strategy is carried out based on a comprehensive objective function which is constructed for reservoirs. Corresponding constraints and conditions are generally designed, and then the solution of the objective function is worked out based on those constraints and finally an optimal scheduling scheme suitable for reservoirs is acquired in combination with actual conditions. Focusing on the problems above, this study combines Dijkstra algorithm with genetic algorithm (GA) effectively and makes full use of their advantages. Consequently, an optimized Dijkstra - genetic algorithm (D – GA) is obtained and applied in the scheduling scheme. First of all, the thesis preliminarily introduces relevant algorithms on water conservancy project and sets up a data model consistent with the actual situation. Secondly, this work analyzes the two algorithms, improves the Dijkstra algorithm and applies D – GA to solution optimization. Thirdly, this study compares the results obtained by using D – GA and GA respectively and finally completes the simulation of water conservancy scheduling system.