Future difficulties related to water utilization in sustainable cities will be influenced by factors such as urban development, climate change, and resource scarcity. Distribution accounts for 80–85% of the entire cost of a water supply system, making it a crucial part of all urban water systems. To increase system reliability, water distribution systems (WDS) are typically designed with the "worst scenario" or "robustness" in mind. Because deterministic assumptions are historically incorrect, a new design methodology that acknowledges uncertainty and provides greater flexibility is needed. To design WDS that are more adaptive, a Genetic Algorithm Flexibility Optimization (GAFO) model is created in Visual C++ and connected to EPANET. In contrast to classical GA optimization, GAFO uses a dynamic decision-making method to maximize a WDS's versatility at the lowest possible cost while taking into account a variety of potential future scenarios. The result is a WDS that may develop a staged implementation strategy that enables a gradual evolution of the WDS over time and follows various future trajectories (changing conditions). The convergence and flexibility of the GAFO model were determined to be good after it was tested on several fictitious scenarios. In comparison to traditional, non-flexible designs, cost reductions of 35% to 72% were achieved. DOI: https://doi.org/10.52783/pst.386