Deep Learning Multi-objective Optimization for Smart Manufacturing via Elitist Genetic Algorithm

This paper proposes a deep learning multi-objective optimization (DL-MOO) method for smart manufacturing to generate wire electrical discharge machining (WEDM) parameters via an elitist genetic algorithm with the deep neural network (DNN) and the transfer learning mechanism. Given multiple objectives, the proposed method can generate WEDM manufacturing parameters to optimize the multiple objectives at the same time. Practical experiments are conducted to validate the proposed method.