Design Optimization Of N-shaped Roof Trusses

Design optimization of a class of plane trusses called the N-Shaped Truss (NST) is addressed. The parametric model of NST presented is intended for real-world application, avoiding simplifications of the design details that compromise the applicability. The model, which includes twenty-seven discrete variables concerning topology, configuration and sizing of the truss, presents a challenging optimization problem. Aspects of such challenge include large search space dimensionality, absence of a closedform objective function and constraints, multimodal objective function and costly CPU time per objective function evaluation. Three implementations of general-purpose genetic algorithms (GA) are tested for this problem, along with a version of taboo search called reactive taboo search (RTS). The RTS exhibited better performance than the tested versions of GA. Performance study of the algorithms provides some good insight to some weaknesses in GA and RTS as well as future prospective combination of them to gain better performance.