Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (13): 160-167.DOI: 10.3778/j.issn.1002-8331.1702-0187

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Hybrid ant colony optimization for flexible robotic manufacturing cell scheduling problem

YANG Yujun, CHEN Ye   

  1. School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510006, China
  • Online:2018-07-01 Published:2018-07-17


杨煜俊,陈  业   

  1. 广东工业大学 机电工程学院,广州 510006

Abstract: This paper addresses the flexible robotic manufacturing cell scheduling problem with multiple robots. A modified disjunctive graph is applied to represent the whole characteristics and constraints of such considered problems. The paper proposes a hybrid ant colony optimization combined with genetic operator and multi-robot schedule algorithm to deal with machine selecting, operation scheduling and robot assignment. In this proposed algorithm, a mixed selection strategy, an adaptive pseudo-random proportional rule and an improved pheromone updating rule are presented in order to solve this scheduling problem. The computational results show that the proposed algorithm is more efficient and more reliable than other methods compared.

Key words: ant colony optimization, multi-robotic, Flexible Job-shop Scheduling Problem(FJSP)

摘要: 在柔性作业车间调度问题的基础上,考虑多台搬运机器人执行不同工序在不同机床之间的搬运,形成柔性机器人作业车间调度问题,提出混合蚁群算法。用改进析取图对问题进行描述,使用混合选择策略、自适应伪随机比例规则和改进信息素更新规则优化蚁群算法,结合遗传算子完成机床选择和工序排序。使用一种多机器人排序算法完成搬运机器人分配和搬运工序排序。通过多组算例仿真测试并与其他算法进行比较,验证了算法的有效性和可靠性。

关键词: 蚁群算法, 多搬运机器人, 柔性作业车间调度问题(FJSP)