Cellular Automata Simulation of RGV Dynamic Scheduling Model

Abstract

For the RGV intelligent scheduling problem, this paper uses a heuristic search algorithm and a cellular automaton to simulate its scheduling process. For the processing of materials in one process, based on the queuing theory short service priority service criterion (SJF), the cellular automata simulation was carried out on the CNC loading and unloading situation of RGV reflected in different processing materials, with continuous operation time per shift (The heuristic priority search algorithm with T=8h) production quantity and RGV waiting time as the evaluation function yields an optimal solution scheduling scheme. For the processing of two material processes, this paper considers that the intelligent addition system has two different processes. The number and location of CNCs processing different processes will affect the production efficiency rate, which in turn affects the scheduling rules of RGV and redefines them. The cell update rule is obtained, and the optimal scheduling scheme and the CNC position arrangement of different processes are obtained. In the case of possible failure during CNC reprocessing, the CNC position of the fault is generated by the random seed of the computer during the simulation process, and the fault duration is processed. Considering that the fault occurs is a random factor, under the specific operating parameters, In these two cases, the RGV dynamic model in this case is randomly simulated by a computer, and the expected value of the maximum material for each shift of the continuous operation time and the expected number of unfinished materials after the failure occur are obtained.