Optimization of multi-pass turning parameters through an improved flower pollination algorithm

The multi-pass turning process is one of the most widely used machining methods in modern manufacturing industry, and selecting proper values for the machining parameters used in this operation such as cutting speed, feed rate, and depth of cut is a very important and difficult task. In this paper, an improved flower pollination algorithm is proposed for solving this problem. With keeping the global search operator and the local search operator of the basic flower pollination algorithm, the proposed algorithm utilizes a new population initialization method which is based on the good point set theory, and utilizes Deb's heuristic rules to deal with the existing constraints. The proposed algorithm inherits the simplicity of the basic flower pollination algorithm. A famous model, which takes the unit production cost as the minimizing objective and involves some practical constraints, is used to examine the efficiency of the proposed algorithm. In addition, the obtained results are compared with some previously published results to examine the superiority of the proposed algorithm. The experimental and comparative results suggest that the proposed algorithm has outstanding performance and practical value.