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Flood control operation of reservoir groups is a complex nonlinear optimization problem involving multiple dimensions,variables,and stages,and plays a vital role in developing efficient and stable methods to enhance the overall flood control capacity of river basins.Whale optimization algorithm (WOA) is an innovative evolutionary algorithm inspired by whale predation behaviors.However,when it is employed to solve flood control operation,problems of premature convergence and proneness to fall into local optimum will occur.To this end,this paper proposes an adaptive-mutation whale optimization algorithm (AWOA) for solving the flood control operation of reservoir groups.In AWOA,an enhanced chaotic strategy is adopted to ensure the dispersion and uniformity of the initial operation scheme.Secondly,a reverse oscillation mutation strategy is utilized to enhance the global search ability.Finally,an adaptive weight strategy is leveraged to realize local fine exploration.Classical test functions and typical operation scenarios in West River show that the proposed method has significant peak shaving effects under various scenarios.With a fast convergence rate and high search accuracy,AWOA provides a novel and practical method for solving the flood control operation of reservoir groups. |
