Determination of Optimal Parameters for Finite Plates with a Quasi-Square Hole

This paper aims at optimizing the parameters involved in stress analysis of perforated plates, in order to achieve the least amount of stress around the square-shaped holes located in a finite isotropic plate using metaheuristic optimization algorithms. Metaheuristics may be classified into three main classes: evolutionary, physics-based, and swarm intelligence algorithms. This research uses Genetic Algorithm (GA) from evolutionary algorithm category, Gravitational Search Algorithm (GSA) from physics-based algorithm category and Bat Algorithm (BA) from Swarm Intelligence (SI) algorithm category. The results obtained from the present study necessitate the determination of the actual boundary between finite and infinite plate for the plates with square-shaped holes. The design variables such as bluntness, hole orientation, and plate dimension ratio as effective parameters on stress distribution are investigated. The results obtained from comparing BA, GA and GSA indicate that BA as SI algorithm category competitive results, proper convergence to global optimal solution and more optimal stress level than the two mentioned algorithms. The obtained results showed that the aforementioned parameters have a significant impact on stress distribution around a square-shaped holes and that the structure’s load-bearing capability can be increased by proper selection of these parameters without needing any change in material properties.