The architecture, engineering, and construction sector has stressed the concepts of efficiency and sustainability because of the industry's high resource consumption. Efficiency is a major criterion for building large-scale structures in order to meet performance requirements while using the least amount of structural material. With the emergence and development of computer tools, mathematical computation-based structural optimization has become a popular way of designing sustainable and efficient buildings. Classical and traditional procedures might not always produce an optimal solution effectively because optimization problems are often non-linear, discontinuous and complex. As a result of their versatility, metaheuristic algorithms have grown in popularity, notably in the engineering profession. The effectiveness of different meta-heuristic algorithms, including the Genetic Algorithm (GA), Simulated Annealing (SA, and Estimation of Distribution Algorithm (EDA), is investigated in this work. As a case study, a parametric arch structure is utilized. Numerical results are achieved by minimizing structural weight while checking that the Von Mises stress is lower than the yielding limit all along the arch. Three single-objective algorithms are used in the study, and their performance is objectively evaluated. The parametric modeling, structural analysis, and optimization phases are conducted entirely in the virtual environment offered by the software packages Rhino, Grasshopper, Karamba, and Galapagos. These interoperable software programs were chosen because of their flexibility, customizability, and widespread usage in engineering and architectural offices, making the techniques and findings of this study valuable to design practitioners.