Research on Two-stage RGV Scheduling Based on Simulated Annealing and Tabu Search

Abstract

The scheduling problem of an intelligent machining system, with multiple Computerized Numerical Control Machine(CNCs) and one Rail Automatic Guidance Vehicle(RGV) with manipulator as its core, in a deterministic environment is studied. It is necessary to determine the ratio of the number of CNCs responsible for the first stage to the number of CNCs responsible for the second stage, the location and the moving path of the manipulator. Starting from the scheduling theory of parallel machines, the RGV algorithm based on simulated annealing is used to determine the optimal route of RGV by analyzing the type of machines and the processing time of work pieces. The experimental results show that the scheduling rule can effectively improve the efficiency of intelligent workshop.