Abstract Submission: This research investigates the optimization of water distribution networks using Genetic Algorithms (GA) integrated with EPANET, with the goal of enhancing both operational efficiency and cost-effectiveness. The core of this study focuses on addressing two key objectives: minimizing headloss and reducing overall system costs, both of which are critical for ensuring optimal performance in water distribution systems. By conducting simulations across various scenarios, the study examines the impact of key design parameters, such as pipe diameter, on network performance. The GA methodology contributes to the search for solutions to water distribution network design challenges, innovating on traditional optimization techniques in its ability to identify more efficient and effective system designs. The results point towards substantial improvements in reducing both energy consumption and material costs, both valuable resources during a fight to mitigate the effects of climate change. By using GA optimization techniques, this method promotes better resource management, contributing to the long-term sustainability of urban water systems. The adaptability of the study's methodology to other network optimization problems further underscores its value for engineers and urban planners seeking to enhance the performance of infrastructure systems. By providing a more efficient system for decision-making, this research contributes to the field of water distribution network optimization, helping encourage future applications in similar systems.
