Optimized Design of Finite Isotropic Plates with Hexagonal Cutout by Metaheuristic Algorithms

This paper aims at optimizing the finite isotropic plates with the hexagonal cutout subjected to plane loading using metaheuristic optimization algorithms. This research uses Differential Evolution Algorithm (DE) and Harmony Search Algorithm (HSA) from the evolutionary algorithm category, Big Bang- Big Crunch Algorithm (BB-BC) from the physics-based algorithm category, and Grey Wolf Optimizer Algorithm (GWO) and Particle Swarm Optimization (PSO) from the SI algorithm category; then the results of these algorithms are compared with each other. The results indicate that the grey wolf optimizer has the complete performance, short solution time and the ability to avoid local optimums. In the analysis of finite isotropic plate, the effective parameters on stress distribution around the hexagonal cutouts are cutout bluntness, cutout orientation, plate’s aspect ratio, cutout size, and type of loading. In this study, with the assumption of plane stress conditions, the analytical solution of Muskhelishvili’s complex variable method and conformal mapping is utilized. The plate is considered to be finite (the proportion ratio of the diameter of circle circumscribing to the longest plate side should be more than 0.2), isotropic, and linearly elastic. The finite element method has been used to check the accuracy of the results. Numerical results are in a good agreement with those of the present analytical solution. The results show that by selecting the aforementioned parameters properly, less amounts of stress could achieve around the cutout can lead to an increase in the load-bearing capacity of the structure.