Optimal design of a 3D-printed scaffold using intelligent evolutionary algorithms

- The aggregated artificial neural network was used to investigate the simultaneous effects of printing parameters on the compressive strength and porosity of scaffolds.
- Particle swarm optimization algorithm was implemented to obtain the optimum topology of the AANN. Pareto front optimization was used to determine the optimal setting parameters.
- The presented results and discussion can give informative information to practitioners who want to design a porous structure, and need to know the impact of influential design parameters.