This chapter emphasizes how metaheuristic algorithms are becoming increasingly important in optimizing reinforced concrete structures, an essential but complex part of structural engineering. Traditional methods often struggle because RC systems are high-dimensional and behave in nonlinear ways. Inspired by nature, biology, and physical processes, metaheuristics offer strong alternative approaches that can efficiently explore large design options to find the best, or nearly the best, solutions. This chapter proposed a detailed vision of different types of metaheuristic algorithms, including evolutionary, swarm-based, human-inspired, physics-based, and hybrid techniques, and how they are used in RC design. Literature reviews are also proposed to show how these algorithms help reduce costs, save materials, and cut environmental impacts, all while keeping safety and performance in check. Using these methods alongside traditional engineering workflows shows their real-world benefits and opens up exciting possibilities for smarter, automated structural optimization in the future.