Application of Multi-Strategy Based Improved DBO Algorithm in Optimal Scheduling of Reservoir Groups

Aiming at the problems of high dimensionality, multi-constraint, multi-phase, non-linearity, and the fact that the established model is not easy to solve for the optimal scheduling of reservoir group flood control, this paper improved the dung beetle optimization algorithm by adopting a variety of strategies, proposes a new intelligent optimization algorithm, the multi-strategy improved dung beetle algorithm (MIDBO), and firstly applied it to the optimal scheduling of flood control in reservoir groups. In addition, this study analyzed and contrasted the MIDBO algorithm's calculation results with the examples of the particle swarm and dung beetle optimization algorithms in relation to the reservoir cluster in the middle and lower sections of the Yellow River. And the peak reduction rates of these algorithms are 52.82%, 51.48%, and 50.25% in turn. The outcomes demonstrate that the MIDBO algorithm has strong performance, fast optimization efficiency, obvious peak reduction effect, and is a feasible method to solve the optimization problem of reservoir flood control and scheduling.