Improved adaptive genetic algorithm for cutter allocation problem of CNC in FMS

Abstract

Cutter is an important component part of the flexible manufacturing system, so the selection of cutters would have direct effect on the machining efficiency and production cost to the whole system. In this paper, a mathematical model for cutter allocation of CNC machining center in FMS is presented, in which the optimization objective is to minimize the total cost of production. Furthermore, the factors of job delivery time and parallel processing of working steps are included in the model. Based on the model, an improved adaptive genetic algorithm is designed and developed to solve the problem to accelerate the speed of the algorithm's convergence and improve the solution efficiency. Finally, the results of the example validations indicate the correctness and effectiveness of the model and the algorithm. This research provides a suitable way for the cutter allocation problem of flexible manufacturing system.