@inproceedings{c7841a2ed2684d4dad7c3c7ea8bf39cf,
title = "Research on process route optimization method based on improved hybrid genetic algorithm",
abstract = "Aiming at the problems of high manual participation and long time-consuming sequencing in the process planning of typical spacecraft parts, a process route optimization method based on improved hybrid genetic algorithm is proposed. By analyzing the relationship between parts' machining features, the machining method of machining features is disassembled into steps and a step forward graph is established, and the initial process route is generated based on the constraints of state change rules. The optimization objective function considering the use cost and replacement cost of processing resources is constructed. Aiming at the problem of process route decision-making, the coding method of adding step sequence information and processing resource information is proposed. In order to ensure that the process route sequence meets the process rule constraints, the OBX crossover operator is used to construct the adaptive mutation operator, and the improved hybrid genetic algorithm is constructed by using the artificial bee colony algorithm for process route optimization. The feasibility of the method is verified by taking a spacecraft cabin part as an example.",
keywords = "adaptive variation, genetic algorithms, heuristic algorithm, process planning",
author = "Lin Wang and Yueyan Liu and Hao Cheng and Yongjian Zhang and Rui Wang and Zujie Zheng",
note = "Publisher Copyright: {\textcopyright} 2023 SPIE.; 4th International Conference on Signal Processing and Computer Science, SPCS 2023 ; Conference date: 25-08-2023 Through 27-08-2023",
year = "2023",
doi = "10.1117/12.3012247",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Anand Nayyar and Hoshang Kolivand",
booktitle = "Fourth International Conference on Signal Processing and Computer Science, SPCS 2023",
address = "美国",
}