Application of Genetic Algorithms (GA) for the Optimization of Riveted Joints

Abstract

Genetic algorithms have an effective search technique in a predefined research space based on natural selection theory. They use the same combination of selection, recombination, and mutation to evolve a solution to a problem. In this study, it has been demonstrated how to determine the optimal diameter, sheet thickness, and sheet width in riveted joints by means of genetic algorithms (GA). In this study the optimization of objective function for the variables in predetermined limit ranges was applied. Since the algorithms developed by this way are based on a principle to find out the best within a range like genetic process, it is becoming possible to predict the most suitable values for riveted junction dimensions in the defined limit range. The algorithms were restrained considering rivet diameter, thickness and width of the sheet, shear strength, tensile strength, and tear hazard of the sheet.