A Python script for adaptive layout optimization of trusses

Numerical layout optimization employing an adaptive 'member adding' solution scheme provides a computationally efficient means of generating (near-)optimum trusses for problems involving single or multiple load cases. To encourage usage of the method, a Python script is presented, allowing medium to large-scale problems to be solved efficiently. As well as handling multiple load cases, the short (98 line) script presented can tackle truss optimization problems involving unequal limiting tensile and compressive stresses, joint costs, and non-convex polygonal domains, with or without holes. Various numerical examples are used to demonstrate the efficacy of the script presented.