Metaheuristics is a method of optimization approximating solutions to problems with high levels of complexity. Solutions are generated through multiple iterations of trial and error derived through randomly generated inputs optimizing outputs through diversification and intensification or, exploration and exploitation. The goal of the application of a metaheuristic function is to generate feasible solutions within an acceptable time scale. This investigation is intensified focusing on metaheuristic algorithms and their application to the field of architecture in a method explore the relationship between inputs of physical parameters such as forces, and the output of physical form. Through a case study using a plug-in in Grasshopper employing bi-directional evolutionary structural optimization, the study discusses how to address challenges to apply metaheuristic algorithms in architectural design including available data, quality of data, and time.