Collaborative Manufacturing Unit Selection Using a Sorting Adaptive Genetic Algorithm in Networked Environment
In order to solve the collaborative manufacturing unit (CMU) selection problem in the networked cooperative manufacturing environment, a sorting adaptive genetic algorithm is proposed. To obtain the optimal executive manufacturing process, the objective function is constructed considering manufacturing cost and product load rate of candidate CMUs under time-sequence constraint. The embedded subtask scheduling procedure in sorting adaptive genetic algorithm is used to ascertain the penalty cost for the tardiness of the task. Finally, a case study is implemented to verify the feasibility of the proposed approach. The results show that the proposed model and algorithm can obtain satisfactory solutions.
Fan Rui, Qiao Lihong, Chen Huawei, Ochi Akio, Usuki Hiroshi and Sekiya Katsuhiko
F. Q. Cheng and F. F. Ye, "Collaborative Manufacturing Unit Selection Using a Sorting Adaptive Genetic Algorithm in Networked Environment", Key Engineering Materials, Vols. 407-408, pp. 230-233, 2009