Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (21): 59-67.DOI: 10.3778/j.issn.1002-8331.2103-0390

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Recent Advances in Scheduling Optimization of Automated Guided Vehicles in Manufacturing Workshops

CAO Lijia, LIU Yang   

  1. 1.School of Computer Science and Engineering, Sichuan University of Science & Engineering, Yibin, Sichuan 644000, China
    2.Artificial Intelligence Key Laboratory of Sichuan Province, Zigong, Sichuan 643000, China
    3.School of Automation and Information Engineering, Sichuan University of Science & Engineering, Yibin, Sichuan 644000, China
  • Online:2021-11-01 Published:2021-11-04



  1. 1.四川轻化工大学 计算机科学与工程学院,四川 宜宾 644000
    2.人工智能四川省重点实验室,四川 自贡 643000
    3.四川轻化工大学 自动化与信息工程学院,四川 宜宾 644000


With the development of production automation in manufacturing enterprises, Automatic Guided Vehicle(AGV) has become the significant role in transportation and handling. In recent years, the key step of scheduling optimization of AGV in manufacturing workshops is to establish the optimization model of double-objective or multi-objective function, which is solved by intelligent optimization methods, in which genetic algorithm has become the most popular algorithm framework because of its exploration ability. In addition, hybrid methods are also widely used, because of these methods make the advantages of various algorithms and operators together and aim to achieve better optimization performance. The models of the latest AGV scheduling optimization in manufacturing workshops and the mainstream optimization results are summarized in this paper. The research methods presented to solve the optimization model are divided into three categories:algorithms based on the framework of genetic algorithm, other intelligent optimization methods and other optimization methods. In each category, important keywords and interdisciplinary vocabularies are extracted and summarized. Furthermore, the two disadvantages in the current research on AGV scheduling and many suggestions for the future research direction combined with the current hot spots(big data, artificial intelligence, et al.) are also given at the end of this article.

Key words: manufacturing workshops, automated guided vehicle, scheduling, intelligent optimization, genetic algorithm, hybrid method



关键词: 制造车间, 自动导引车, 调度, 智能优化, 遗传算法, 混合算法