Optimal Layout of the Irregular Parts with Neural Networks Hybrid Algorithm

Abstract

An irregular parts optimal layout method based on artificial neural networks is proposed. The manufacturing process of parts is involved in the layout problem. Every side of shapes is expanded in consideration of the machining allowance. Self-Organizing Map (SOM) and Hopfield artificial neural network are integrated to complete the automatic layout. In the beginning, irregular parts are randomly distributed. Self-Organizing Map is used to look for the best position of the irregular parts by moving them. The overlapping area is gradually reduced to zero. Hopfield neural network is used to rotate each part, and each part's optimum rotating angle is obtained when the neural network is in stable state. The algorithm in this paper can solve the irregular parts layout problem and rectangular parts layout problem in the given region. Examples indicate that this algorithm is effective and practical.