Dynamic Scheduling Model of Intelligent Rail-Guided Vehicles Based on Dynamic Programming

Rail-guided vehicles (RGVs) is widely used in logistics production processes to process Computer number controllers (CNCs). How to use RGV with maximum efficiency is an urgent problem to be solved. The objective of this paper is to establish and evaluate the RGVs scheduling strategies of a flexible manufacturing system (FMS). To tackle this problem, this paper comprehensively uses the enumeration method, traversal search, state transition judgment, global optimization and computer simulation, based on dynamic programming model, to establish an RGV dynamic scheduling model. Then we establish an algorithm to solve the model. Data-based computer simulations are used to test the proposed model. The experimental results show that the model has good practicability and the algorithm is effective.