Instructional Mutation Ant Colony Algorithm in Application of Reservoir Operation Chart Optimization

Guided by the chart that made according to the conventional method, the reservoir operation often cannot develop the maximum economic benefits, and a certain optimizing space exists in such a chart. Based on the basic ant colony algorithm (ACA), the mutation part improved with instruction in this paper was applied to the optimization of reservoir chart to auto-adjust the dispatching line. The improvement enhances the global search ability of algorithm and makes full use of the historical and observed data, so that the algorithm can converge to the global optimal solution faster and better. Through the application, the instructional mutation ACA (IMACA) verifies the obvious optimization effect of the reservoir chart and remarkable economic benefit.