An Enhanced Multioperator Runge–Kutta Algorithm for Optimizing Complex Water Engineering Problems

Water engineering problems are typically nonlinear, multivariable, and multimodal optimization problems. Accurate water problem helps predict these systems’ performance. This paper proposes a novel algorithm named enhanced multioperator Runge–Kutta (EMRUN) to accurately solve different types of The EMRUN’s novelty is focused mainly on enhancing the exploration stage, utilizing search mechanism (RK-SM), covariance matrix adaptation evolution strategy (CMA-ES) techniques, improving exploitation stage by using solution quality (IESQ) sequential quadratic programming (SQP) methods. In addition that, adaptive parameters were included improve stability two stages. superior performance EMRUN initially tested against set CEC-17 benchmark functions. Afterward, proposed extracts from an eight-parameter Muskingum model. Finally, EMRUM applied practical hydropower multireservoir system. experimental findings show that performs much better than advanced approaches. Furthermore, has demonstrated ability converge up 99.99% global solution. According findings, suggested method competitive should be considered in optimizing