Abstract
Metaheuristic algorithms (MH) are widely used in engineering applications due to their global search capabilities and independence from gradient information. Truss structures are commonly used in structural design, and the best solution typically involves minimizing the weight while ensuring adequate strength and stiffness. To achieve this goal, several hybrid MH algorithms have been proposed by combining the strengths of two or more algorithms. In this paper, we propose a hybrid social network search (SNS) and material generation algorithm (MGA) for truss structure optimization. The main levels as parallel and series levels are defined for the hybrid algorithm. The proposed algorithm is evaluated using several benchmark truss structures, and the results demonstrate its superiority over other state-of-the-art MH algorithms.
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