@article{XIA2022, 
author = {Qinxiang XIA and Kai LI and Jun MA and Xiuquan CHENG and Gangfeng XIAO},
title = {Die Electrode Scheduling Problem Solution Based on Genetic Algorithm},
year = {2022},
journal = {Journal of South China University of Technology (Natural Science Edition)},
volume = {50},
number = {3},
pages = {80-87},
keywords = {die electrodes scheduling, tardiness, correlation principle, genetic algorithm, strategy of breeding},
url = {https://www.sciopen.com/article/10.12141/j.issn.1000-565X.210284},
doi = {10.12141/j.issn.1000-565X.210284},
abstract = {In view of the scheduling problem of die electrode in CNC and EDM stages, a mathematical model with batch processing and correlation characteristics was established. To minimize the tardiness of die parts, the solving process of die electrode scheduling problem was divided into two stages: batch processing and batch scheduling. In the first stage, the batch processing problem was solved according to the principle of correlation, and the correlation priority batch algorithm was designed. In the second stage, the batch scheduling problem was solved by genetic algorithm, and a strategy based on animal breeding was proposed to improve the traditional genetic algorithm. The die electrode scheduling program was developed based on MATLAB software to realize the above two stages of solving process, and the test was carried out under 24 kinds of simulation examples. The results show that, the designed die electrode scheduling algorithm is effective for solving the batch processing and batch scheduling problem of die electrode; the proposed strategy of breeding can significantly improve the quality of traditional genetic algorithm solution; and the tardiness of die parts in the examples can be reduced by 16.71% at most.}
}