RGV dynamic scheduling model based on kruskal algorithm

摘要

In order to solve the problems in traditional processing industry and meet the increasingly urgent demand for product processing performance,intelligent processing has begun to be widely used in industrial production.Today,the Rail Guided Vehicle (RGV) has become one of the main equipment for logistics distribution tasks in intelligent processing systems.It automatically controls the direction and distance of movement according to the command.By planning the dynamic scheduling model of RGV,the output efficiency of industrial production can be greatly improved.Based on the Kruskal algorithm in the greedy algorithm,we design a set of material processing RGV dynamic scheduling simulation model through C++ programming.According to the theory of “local variable optimization and global variable optimization" in the Kruskal algorithm,the shortest path is selected every time the next target of RGV is judged,so that the whole distance traveled is the shortest,wasting shortest time and achieving the highest output.