摘要
自动引导车(automated guided vehicle,AGV)具有自动化程度高、搬运能力强等优点,被广泛应用于柔性制造车间物料运输。为提高柔性制造车间多台多载具AGV的能效与搬运效率,以能耗和搬运距离为优化目标建立多载具AGV节能调度模型,提出了一种两阶段优化调度方法。该方法基于就近分配和路径重合度相结合方法为各多载具AGV优化分配搬运任务,并基于改进遗传算法对各多载具AGV的装卸任务顺序进行组合优化,从而实现多载具AGV的搬运距离和能耗目标综合优化。案例研究表明,本文提出的两阶段优化方法是有效的。
Automated guided vehicles(AGVs)are widely used for material transportation in flexible manufacturing workshops due to their advantages of high automation and strong handling capacity.To improve the energy efficiency and handling efficiency of multi-load AGVs,an energy-saving scheduling model considering the objectives of energy consumption and handling distance is established,and a two-stage optimal scheduling method is proposed.In the method,a combination of proximity allocation and path coincidence approach is designed to optimize task allocation among multi-load AGVs,and an improved genetic algorithm is proposed to optimize the sequence of loading and unloading tasks.Thus,the comprehensive performance of the handling distance and energy consumption of multi-load AGVs is improved.The case study shows that the proposed twostage optimal scheduling method is effective.
作者
吴立辉
顾天鑫
石津铭
WU Lihui;GU Tianxin;SHI Jinming(School of Mechanical Engineering,Shanghai Institute of Technology,Shanghai 201418,China)
出处
《应用技术学报》
2024年第4期451-458,共8页
Journal of Technology
关键词
柔性制造车间
自动引导车
节能调度
改进遗传算法
flexible manufacturing workshop
automated guided vehicle(AGV)
energy-saving scheduling
improved genetic algorithm
作者简介
吴立辉(1981-),男,副教授,博士,主要研究方向为复杂制造系统调度与控制。E-mail:wulihui@sit.edu.cn。
