This thesis presents a comprehensive study on the optimization of the intake tower structure at the Megech Dam using Genetic Algorithms (GAs). The Megech Dam, located in the Amhara National Regional State of Northwestern Ethiopia, serves as a crucial water supply and irrigation project. The intake tower, a pivotal component of the dam, regulates water flow from the reservoir, making its efficient design essential for the project's success. conventional design methodologies often struggle to address the multifaceted optimization challenges posed by complex structures like intake towers. Genetic Algorithms, however, offer a robust and adaptable solution by simulating the process of natural selection. This research develops and implements a GA-based optimization framework to enhance the structural efficiency and cost-effectiveness of the intake tower. The study identifies critical design parameters, formulates the optimization problem, and constructs the Genetic Algorithm framework, including the encoding of design variables and the application of selection, crossover, and mutation operations. The implementation of the GA is conducted using MATLAB, and the optimized designs are validated through Finite Element Analysis (FEA) using SAP2000. The results demonstrate that the GA-optimized intake tower structure significantly outperforms conventional designs in terms of material efficiency, structural strength, and cost reduction. This optimization not only ensures the successful performance of the Megech Dam project but also sets a precedent for future infrastructure projects in structural engineering. The study highlights the potential of Genetic Algorithms to deliver innovative and practical solutions for complex engineering challenges, contributing to the broader field of civil engineering. Key words: Intake Tower Structure, Reinforced Concrete, Genetic Algorithm, Design Optimization, MATLAB.