In this study, optimum designs of reinforced concrete spread footings bases with minimum cost were realized with various metaheuristic algorithms known as Artificial Bee Colony, Cuckoo Search, Teaching-Learning-Based Optimization Algorithm. The findings obtained from the optimum designs performed by the algorithms are evaluated according to various performance criteria. Teaching-Learning-Based optimization algorithm showed the highest performance and convergence speed. On the other hand, the effect of bending moment-axial force level, bearing capacity of soil on the optimum design of the spread footing are investigated by some parametric studies. It is understood that the increase in axial force increases the minimum cost of the spread footing and the increase in the eccentricity level rises the degree of increase. It has been observed that the minimum cost of spread footing has decreased with the increase of the bearing capacity of soil.