Accelerating multi-objective optimization of concrete thin shell structures using graph-constrained GANs and NSGA-II.

In architectural and engineering design, minimizing weight, deflection, and strain energy requires navigating complex, non-linear interactions among competing objectives, making the optimization of concrete thin shell constructions particularly challenging. Traditional multi-objective optimization (MOO) methods frequently encounter difficulties in effectively exploring design spaces, which often necessitate substantial computational resources and result in suboptimal solutions. This paper presents a novel approach for enhancing topology and thickness optimization.