文献类型：期刊文献

英文题名：Research on Multi-objective Dynamic Scheduling in Workshops Based on Depth Learning

作者：Ren, Jianfeng[1,2];Ye, Chunming[1]

第一作者：Ren, Jianfeng;任剑锋

通讯作者：Ren, JF[1];Ren, JF[2]|[1048412820815e1]任剑锋;

机构：[1]Univ Shanghai Sci & Technol, Business Sch, Shanghai, Peoples R China;[2]Henan Univ Econ & Law, Sch Comp & Informat Engn, Zhengzhou, Henan, Peoples R China

第一机构：Univ Shanghai Sci & Technol, Business Sch, Shanghai, Peoples R China

通讯机构：[1]Univ Shanghai Sci & Technol, Business Sch, Shanghai, Peoples R China;[2]Henan Univ Econ & Law, Sch Comp & Informat Engn, Zhengzhou, Henan, Peoples R China.|[1048412]河南财经政法大学计算机与信息工程学院;[10484]河南财经政法大学;

年份：2018

卷号：21

期号：2

外文期刊名：JOURNAL OF ADVANCED OXIDATION TECHNOLOGIES

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000433154903049)】；

语种：英文

外文关键词：Deep Learning; Dynamic Scheduling; Genetic Algorithm

摘要：Computer technology has been developed continually and used more and more widely in production. The multi-objective dynamic scheduling in workshops was studied based on depth learning and it was mainly studied from workshop robot scheduling in this article. The fuzzy obstacle avoidance navigation method suitable for dynamic complex environment was first proposed. And the fuzzy rules of this method were based on the experience of human driving. Secondly, aiming at the obstacle avoidance navigation task with high path optimization, a robot dynamic scheduling method based on genetic algorithm optimized artificial potential field was proposed. Finally, the simulation experiment was carried out and the conclusion was obtained: the dynamic scheduling method designed in this paper can effectively plan and schedule the workshop robot.