A Guided Ant Colony Optimization Algorithm for Conflict-free Routing Scheduling of AGVs Considering Waiting Time

Li Junjun, Xu Bowei, YANG Yongsheng, Wu Huafeng


Efficient conflict-free routing scheduling of automated guided vehicles (AGVs) in automated logistic systems can improve delivery time, prevent delays, and decrease handling cost. Once potential conflicts present themselves on their road ahead, AGVs may wait for a while until the potential conflicts disappear besides altering their routes. Therefore, AGV conflict-free routing scheduling involves making routing and waiting time decisions simultaneously. This work constructs a conflict-free routing scheduling model for AGVs with consideration of waiting time. The process of the model is based on calculation of the travel time and conflict analysis at the links and nodes. A guided ant colony optimization (GACO) algorithm, in which ants are guided to avoid conflicts by adding a guidance factor to the state transition rule, is developed to solve the model. Simulations are conducted to validate the effectiveness of the model and the solution method.


Ant colony Automated guided vehicles Conflict-free Particle swarm optimization Routing scheduling Waiting time

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DOI: http://doi.org/10.11591/ijra.v6i2.pp69-79


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IAES International Journal of Robotics and Automation (IJRA)
ISSN 2089-4856, e-ISSN 2722-2586
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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