Currently, a wide range of optimization strategies are being employed across many domains. Optimization methods have a long history, dating back to the development of calculus, and have gained significant recognition in the era of digital technology. On the other hand, the resources spent for concrete production are enormous creating various setbacks worldwide. Fiber-reinforced concrete (FRC) has attracted considerable interest within the construction sector owing to its augmented characteristics, including greater tensile strength, crack resistance, and durability. The volume percentage of fibers scattered inside the concrete matrix is a critical factor that significantly impacts the performance of fiber-reinforced concrete (FRC). Attaining an ideal volume percentage of fibers is imperative in order to maximize the mechanical characteristics of the material, while also taking into account the constraints imposed by the concrete matrix. Among other researches regarding the research problem, an attempt has been made to optimize the volume fraction of fibers in concrete using an evolutionary algorithm—genetic algorithm. The primary aim of this study is to develop a fundamental objective function that can be used to minimize the volume fraction of fibers in fiber-reinforced concrete. The GA technique is implemented using MATLAB, mostly because of its adaptability and effectiveness in addressing optimization challenges. There is a deliberate attempt to reduce the proportion of fibers within the given restrictions. A parametric study was conducted to examine the impact of various parameters on fiber-reinforced concrete. The findings of this study show promising results, which can contribute to the development of resilient structures with optimized resources.