Traditional grey infrastructure has shown significant limitations in responding to complex disaster chains due to neglecting the synergistic effects of natural hydrological processes and ecosystem services.Green infrastructure （GI），by leveraging natural processes for regulation and achieving multi-functional synergy，was regarded as an effective way to overcome these limitations.This article took Zhengzhou City as an empirical case to develop a framework for the optimization of planning GI for flood-resilience that integrates multi-criteria decision-making and evaluation with genetic algorithm.An indexes system was constructed from four dimensions including the natural geography and climatic baseline，infrastructure sensitivity，natural environmental response，and the socio-economic impacts.A spatial deployment priority model of GI was built on a GIS platform.On this basis，a genetic algorithm was introduced to perform quantitative optimization of the types and scales of GI for flood-resilience within each priority zone under multiple objectives and constraints to obtain near-optimal GI layout schemes for different regions.The results showed that the proposed framework can effectively identify the high-priority deployment areas and key control zones of GI for flood-resilience in Zhengzhou City while simultaneously considering the safety of flood-resilience and construction constraints，optimize the portfolio configuration of different types of GI，and achieve a closed-loop planning process from spatial priority identification to type allocation optimization.It is confirmed that coupling multi-criteria spatial evaluation with a multi-objective genetic algorithm can provide quantifiable basis for planning and decision-making，and replicable computational framework for improving flood-resilience in high-density megacities.It will provide a transferable technical reference for constructing the layout of flood-resilience-oriented GI in other rapidly urbanizing areas of the same type.