Multi-objective truss structural optimization considering dynamic and stability behaviors and automatic member grouping

Resumo

This paper aims to address the challenge of multi-objective structural optimization in the search for the most efficient configuration of members in truss structures. Conflicting objectives, such as the structure's weight, the number of discrete cross-sectional areas, the first natural vibration frequency, and the first load factor relative to overall structural stability, must be optimized simultaneously, resulting in a Pareto Front (PF) that provides non-dominated solutions. NSGA-III is the multi-objective evolutionary algorithm adopted to solve the proposed optimization problems. Non-dominated solutions are extracted from the FP using multi-criteria decision-making (MCDM). New competitive configurations of structural members can be discovered, offering attractive alternatives to decision-makers in manufacturing, cutting, transportation, checking, and welding.