A Multi-AGV Optimal Scheduling Algorithm Based on Particle Swarm Optimization

Abstract

With the increasing use of AGV in industrial automation system, it is necessary to study reasonable task allocation plan and optimized scheduling of AGV to ensure efficient transportation. This paper proposes a multi-AGV optimal scheduling algorithm based on particle swarm optimization in intelligent warehousing system. Based on the analysis of the operating mechanism of the AGV equipment and the scheduling requirements of the warehouse environment, a mathematical model is established to optimize the scheduling strategy. The minimum value of the objective function of the optimization problem is obtained by using the particle swarm optimization algorithm, that is, the time for the multi-AGV to complete the transportation task in the fixed cycle is the shortest. Combining the characteristics of this problem, the particle swarm optimization algorithm is able to enhance the ability of global search and increase the possibility of finding the optimal scheduling strategy. The simulation results show that the proposed algorithm can shorten the AGV waiting time and improve the system operation efficiency, which provides an optimized and practical way for multi-AGV scheduling in warehouse system.