Research on optimization of intelligent stock rack replenishment path based on improved genetic algorithm

Based on the application of intelligent material rack, this paper optimizes the AGV logistics scheduling in the factory, and proposes a genetic method to improve the cross-variation genetic operation. Through experimental comparison, the genetic algorithm based on the improved cross-variation genetic operation has certain advantages compared with the traditional genetic algorithm in the application of AGV logistics scheduling. The replenishment path optimization reduces the time and manpower cost of manual inspection, improves the logistics process, realizes the integration of line-side logistics, fundamentally improves the overall efficiency of line-side logistics in manufacturing final assembly, and reduces logistics costs.