摘要
针对多自动引导车(automatic guided vehicle,AGV)在仓储物流搬运系统中的巷道拥堵问题,提出一种规避拥堵的系统优化策略,将产生的AGV拣货路径作为约束生成后续AGV运行轨迹。对仓库相邻节点赋予时间链接,构建时空网络地图,在此环境建立基于离散时空网络的考虑拥堵的路径优化模型,并设计了时空网络与模拟退火(simulated annealing,SA)相结合的全局优化算法——时空模拟退火(space time simulated annealing,ST-SA)以求解该模型,通过仿真实验对模型及算法的有效性进行验证。实验结果表明:系统优化策略可以对AGV路径规划过程进行控制与优化,ST-SA能够很快搜索到合理、高效的AGV拣货路径方案,缩短AGV在巷道的作业时间,避免了多AGV在智能仓储系统中的碰撞及拥堵。
Aiming at the roadway congestion problem of multiple automatic guided vehicle(AGV)in the automated storage and retrieval system,a system optimization strategy to avoid congestion was proposed,and the generated AGV picking path was used as a constraint to generate subsequent AGV running trajectories.Adjacent nodes of the warehouse was assigned time links to build a space-time network map,and a path optimization model was established based on discrete space-time networks in this environment,which considered congestion.A global optimization algorithm space time simulated annealing(ST-SA)was designed that combined space-time networks and simulated annealing(SA)to solve the model,and through simulation experiments,the effectiveness of the model and algorithm was proved.The experimental results show that the system optimization strategy can control and optimize the AGV path planning process.ST-SA can quickly search for a reasonable and efficient AGV picking path plan,reduce the AGV's working time in the roadway and avoid multiple AGVs collision and congestion in the automated storage and retrieval system.
作者
徐翔斌
李紫阳
XU Xiang-bin;LI Zi-yang(School of Transportation and Logistics, East China Jiaotong University, Nanchang 330013, China)
出处
《科学技术与工程》
北大核心
2021年第33期14209-14219,共11页
Science Technology and Engineering
基金
国家自然科学基金(71761013)
江西省自然科学基金(20181BAB201010)。
关键词
拥堵
系统优化
时空网络
路径规划
congestion
system optimization
space-time network
path planning