A hybrid immune genetic algorithm with tabu search for minimizing the tool switch times in CNC milling batch-processing

摘要

In order to enhance the machining efficiency, batch-processing is widely used in computer numerical control (CNC) milling machining. Each job in a batch requires a set of different tools to be processed, so tool switching is needed during processing. However, the frequent tool switching not only affects the machining efficiency, but also affects the life of the machine spindle. In order to solve this problem, a hybrid immune genetic algorithm with tabu search (HIGATS) integrated is proposed to minimize the tool switch times. In HIGATS, a well-designed encoding/decoding scheme is developed to represent the solution and evaluate the fitness; a novel constructive heuristic is used for initializing population; in order to balance the intensification and diversification, tabu search is integrated into genetic algorithm, and also, a problem-specific greedy immune operator is applied to intensify the searching ability. Simulation experiments are conducted to verify the performance of HIGATS by comparing it with other five algorithms. The results and analyses demonstrate that HIGATS outperforms the other five algorithms in minimizing the tool switch times.