Antlion Algorithm Based on Immune Cloning and Its Truss Optimization

Antlion optimization algorithm has good search and development capabilities, but the influence weight of elite ant lions is reduced in the later stage of optimization, which leads to slower algorithm convergence and easy to fall into local optimization. For this purpose, an antlion optimization algorithm based on immune cloning was proposed. In the early stage, the reverse learning strategy was used to initialize the ant population. The Cauchy mutation operator was added to the elite antlion update to improve the later development ability of the algorithm; finally, the antlion was cloned and mutated with the immune clone selection algorithm to change the position and fitness value of the antlion, and further improve the algorithm's global optimization ability and convergence accuracy. 10 test functions and a 0~1 backpack were used to evaluate the optimization ability of the algorithm and applied to the size and layout optimization problems of the truss structure. The optimization effect was found to be good through the force effect diagram. It is verified that ICALO is applied to combinatorial optimization problems with faster convergence speed and higher accuracy. It provides a new method for structural optimization.This article is submitted as original content. The authors declare that they have no competing interests.

Multi-objective design optimization of additively manufactured lattice structures for improved energy absorption performance

This paper aims to improve the energy absorption performance of stiffness-optimized lattice structures by utilizing a multi-objective surrogate-based size optimization that considers the additive manufacturing (AM) constraints such as the minimum printable size. A truss optimization is first utilized at the unit cell level under static compressive loads for stiffness maximization and two optimized lattice configurations called the Face-Body Centered Cubic (FBCC) lattice and the Octet Cubic (OC) are obtained. A multi-objective size optimization process is then carried out to improve the energy absorption capabilities of those lattice designs using non-linear compression simulations with Nylon12 material to be fabricated by the Multi Jet Fusion (MJF) AM process. Thin plate spline (TPS) interpolation method is found to produce very high accuracy as the surrogate model to predict the highly nonlinear response surfaces of energy absorption objectives in the optimization. Compared to the lattice designs with uniform strut diameters, by using the optimization process, the maximum energy absorption efficiency ( EAEm) and the crush stress efficiency ( CSE) of the OC lattice design are further improved up to 33% and 37%, respectively. The FBCC lattice design is also found to have superior EAEm performance compared to the existing lattice types considered for fabricating by the MJF process in the literature.