A data-driven intelligent algorithm for dynamic path design of automated-guided vehicle systems

The dynamic path design problem of automated-guided vehicle (AGV) systems is one of the most important but difficult issues in the advanced manufacturing system, which was proposed by Gaskins. In this paper, a mathematical model for the dynamic path design problem is developed, and an intelligent solution approach has been presented based on the big-data calculation method. Firstly, the calculation architecture of the big-data is set up. Then, a data-driven intelligent algorithm is adopted to obtain a feasibility near-to-optimal path design solution for multi-AGV system, which considers the total transportation as a main objective. Finally, a complex manufacturing environment is set to verify the efficiency of the proposed data-driven intelligent approach for dynamic path design problem of the multi-AGVs system. The experimental results indicate that the proposed approach can obtain a quite effective for dynamic path design problem.