自动导引车与机器集成调度问题研究现状  

Research Status of AGV and Machine Integrated Scheduling

作　　者：吴斌[1] 丁钰超 ABLA Basri WU Bin;DING Yuchao;ABLA Basri(School of Economics&Management,Nanjing Tech University,Nanjing 211816,China)

机构地区：[1]南京工业大学经济与管理学院,南京211816

出　　处：《计算机工程与应用》2023年第6期1-12,共12页Computer Engineering and Applications

基　　金：国家社科基金一般项目(20BGL025);国家重点研发项目子课题(2020YFB1712102)。

摘　　要：随着自动导引车(automated guided vehicles,AGV)的广泛应用,柔性制造车间中机器设备与AGV之间的协同配合日益受到重视。AGV与机器的集成调度主要研究机器分配、工序排序、搬运任务的AGV分配以及AGV路径规划。该问题是极为复杂的组合优化问题,对其研究具有重要的学术意义和应用价值。围绕问题特征,从模型与算法两个方面,对国内外最新的研究文献进行了梳理。对现有模型中的约束条件和优化目标进行了详细分类,从遗传算法、混合优化算法、仿真优化算法等五个方面综述了现有算法研究中的代表性成果。在此基础上,指出了现有研究中的不足,提出了未来的研究内容和方向。With the wide application of automated guided vehicles(AGV),the cooperation between machines and AGVs in flexible manufacturing system(FMS)is paid more and more attention.The research of AGV and machine integrated scheduling mainly includes machine allocation,process sequencing,AGV allocation of transport tasks and AGV path plan-ning.This problem is a very complex combinatorial optimization problem,which has important academic significance and application value for its research.Based on the characteristics of the problem,the latest research literatures at home and abroad are reviewed from two aspects of model and algorithm.The constraints and optimization objectives of the exist-ing models are classified in detail,and the representative results of the existing algorithms are summarized from five aspects:genetic algorithm,hybrid optimization algorithm and simulation optimization algorithm and so on.On this basis,the short-comings of existing research are pointed out,and the content and direction of future research are put forward.

关 键 词：柔性制造车间 自动导引车 集成调度 智能优化 混合算法 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP391[自动化与计算机技术—控制科学与工程]