To efficiently develop power generation and solve downstream ecological health protection in Qingjiang basin, multi-objective ecological operation for cascade reservoirs (MOEOCR) model is established in contrast to conventional models that set ecological water requirement as constraint. The basic, suitable and ideal ecological water requirements in Geheyan and Gaobazhou sections are calculated using a requirement level index. Instead of the traditional evolution mode based on population, we introduce a shuffled frog leaping algorithm (SFLA) which evolves independently in sub-populations. Moreover, the SFLA is converted into a modified multi-objective algorithm (MMOSFLA) with strategies including chaotic population initialization, renewed frog grouping method and local search method, and elite frog set evolution based on cloud model. The water level corridor is used to help effectively handle complex constraints. The IGD and GD indexes are used to evaluate quality of solutions acquired by each method. In terms of normal year, the mean IGD and GD of MMOSFLA are 1.2 × 10–1 and 2.75 × 10–2, respectively. The scheduling results verify efficient search ability and convergence performance in solution diversity and distribution in comparison with other methods. Therefore, MMOSFLA is verified to provide an effective way to fulfill hydropower and ecological benefits facing the MOEOCR problem.