Cutting parameters optimization based on ITLBO algorithm with big data driven

At present, it is an important method to solve the problem of industrial multi-objective optimization based on data-driven evolutionary, optimization. In this paper, we study the multi-objective optimization problem of CNC cutting based on data-driven teaching and learning based optimization algorithm. Based on the large-scale off-line CNC cutting data to establish the optimization model, using the improved teaching and learning based optimization algorithm (ITLBO) to solve The simulation experimental results show that the optimization results are better.