An integrated scheduling method of multi-AGV in large-scale industrial warehouses

To address the inefficiency of automated guided vehicle(AGV) fleets in large-scale industrial warehouses, an integrated scheduling method based on hierarchical planning was proposed, which decomposed the scheduling problem into an aggregated upper-level task sequencing assignment problem and a lower-level path planning problem. An elite solution set was generated in the upper-level problem, and the tabu list generated by the lower-level path planning was integrated into the iteration search process as collision conflict constraints for upper-level problem. In iteration search processes, the elite solution of the upper-level problem with a large number of collision conflicts obtained by the path planning was continuously excluded by updating the upper-level elite solution set and the lower-level tabu list, to obtain the solution with the best overall performance. Further integrating path search and tabu lists to achieve simultaneous optimization of multiple interrelated problems in AGV scheduling, the effectiveness of the method was verified by a large-scale industrial warehouse case. The results show that, compared to the sequential optimization scheduling method, the completed time and delay time due to collision conflicts of an integrated scheduling method reduce 10.56% and 74.53%, respectivelty. For large-scale problems, compared to the hybrid adaptive large neighborhood search algorithm and the pre-planning algorithm, the task completion time of an integrated scheduling method reduce by 9.73% and 5.54%, respectively, and the computation time reduce by 84.19% and 86.68%, respectively. © 2023 Central South University of Technology. All rights reserved.