Dynamic Schedule Of Rail-Guided Vehicles Based On Genetic Algorithm

The efficiency of conveyor system which connects the multi-layered shelvesand external materials conveyance is crucial for the automated storage and retrievalsystem (AS/RS). To improve the efficiency of conveyor system under large amountof logistics, it was studied on dynamic schedule of RGVs (Rail-Guided Vehicles)which belonged to the conveyor system. Furthermore, it was studied on how tobuild conveyor system reasonably.Firstly, based on the analysis of curial issues of dynamitic schedule of RGVs,eM-Plnat software was chosen to model the AS/RS. So simulation technology canbe used to do further research on dynamitic schedule of RGVs.Secondly, in order to get an optimized scheduling scheme for RGVs, a basicgenetic algorithm was proposed to solving the model. Compared with theFirst-come First-served policy, simulation result demonstrated that the basicgenetic algorithm was more efficiency.Finally, the genetic manipulation of the basic genetic algorithm was improvedto make the schedule more reasonable. Simulation results showed that improvedgenetic algorithm was more efficiency compared with basic genetic manipulation.At the same time, it was studied on how to build conveyor system reasonably on theuse of simulation technology.Simulation results showed that the improved genetic algorithm could get anoptimized scheduling scheme for RGVs to improve the efficiency of conveyorsystem greatly. Besides, transporting capacity of conveyor system could be raisedby increasing number of in/out station and number of RGVs, especially the numberof RGVs. When building conveyor system, best number of stations and RGVs couldbe found by simulation.