Research on Optimization of Multi-AGV Path Based on Genetic Algorithm Considering Charge Utilization

Abstract

The rapid development of e-commerce and artificial intelligence technology has led to the rapid development of unmanned warehousing automation technology in the logistics industry. Unmanned warehousing and automated guided vehicle (AGV) equipment in unmanned warehousing have also increased. Since the AGV needs to be charged, based on the traditional simple path optimization, if the sorting efficiency of logistics needs to be further improved, the charging problem of the AGV needs to be considered. This paper constructs a multi-AGV path optimization model in an unmanned storage environment based on the charging utilization rate. The model takes the shortest path and the highest charging utilization rate as the dual goals, and selects the genetic algorithm as the method to solve the model, which is verified by simulation experiments. The proposed model and algorithm have certain validity and feasibility.