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作 者:梁晓磊 陈壮 李文婷 田梦丹 鄢威 LIANG Xiaolei;CHEN Zhuang;LI Wenting;TIAN Mengdan;YAN Wei(School of Automotive and Traffic Engineering,Wuhan University of Science and Technology,Wuhan 430070,China)
机构地区:[1]武汉科技大学汽车与交通工程学院,武汉430070
出 处:《组合机床与自动化加工技术》2024年第11期187-192,共6页Modular Machine Tool & Automatic Manufacturing Technique
基 金:国家自然科学基金资助项目(51975432,61603280);武汉科技大学“十四五”湖北省优势特色学科(群)项目(2023B0405)。
摘 要:针对智能制造环境下的工业物联网络容易在恶劣工况下出现局部网络连通断裂现象,提出以自动导引小车(AGV)等移动智能物流单元作为中间载体进行异常网络应急修复的任务调度机制,通过考虑网络连通、任务优先级、作业时间窗等约束,构建了具有物流任务和网络修复要求的多阶段AGV连续调度模型。针对该模型,设计了具有深度搜索和莱维飞行探索的改进多子群粒子群算法进行有效求解。通过3类不同规模的案例测试,结果显示所提构建的模型和算法可以有效实现AGV在完成运输任务的同时进行网络应急修复,显著改善工业物联网络连通度,提高网络鲁棒性。Considering that industrial Internet of Things in intelligent manufacturing environment is prone to local network connectivity and rupture under harsh working conditions,a scheduling mechanism using mobile intelligent logistics units such as AGVs as the intermediate carrier for emergency repair of abnormal networks was proposed.Under the constraints of network connectivity,task priority and operation time window,a multi-staged continuous AGV scheduling model with logistics tasks and network repair requirements was constructed.For this model,an improved multi-subgroup particle swarm optimization algorithm with deep search and Lévy flight exploration was designed to solve the model effectively.The test results of different scale cases show that the proposed model and algorithm can effectively realize the AGV to complete the transportation task while carrying out network emergency repair,improve the connectivity significantly of industrial Internet of Things network and enhance the network robustness.
分 类 号:TH165[机械工程—机械制造及自动化] TG659[金属学及工艺—金属切削加工及机床]
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