Design And Configuration Optimization Of Tier-to-Tier Shuttle-based Storage And Retrieval System Based On Artificial Intelligence Forklift Transportation

In the past two years,under the threat of the worldwide epidemic,various countries have generally implemented management and control measures to reduce the unnecessary flow of people,which has promoted the development of the "home economy" represented by home shopping.The transformation of consumption mode also puts forward new requirements for logistics capacity of enterprises.Emerging FMCG industries and some traditional industries with weak capital are considering introducing multi-layer shuttle vehicle system to improve their logistics service level.However,the traditional MSS/RS,which is widely used today,uses shuttle vehicles without crossing floors and uses stationary conveyors as transport equipment.Its poor performance in flexibility and scalability restricts its range of use,and most enterprises can hardly afford its high investment cost,which limits the popularity of MSS/RS system.This paper presents an improved TT-MSS/RS system which adopts artificial intelligence forklift.Compared to the traditional MSS/RS,the new system uses a crossover shuttle and uses an "AI forklift+picking table" as the handling and sorting equipment,replacing the traditional MSS/RS model of using a non-crossover shuttle and a stationary conveyor.The new system improves the flexibility and expansibility of the system on the premise of maintaining the same storage capacity and higher storage capacity.This paper mainly focuses on the system design,performance analysis and configuration optimization of this improved MSS/RS system.The system design includes the overall design of the system,the layout structure and the configuration conditions.According to the physical characteristics of each component of the system,the storage and sorting of two basic operating processes are analyzed.The performance analysis aims to verify the feasibility of the new MSS/RS,and according to the movement law of each component of the system and the connection relationship of the operation process,the hybrid queuing network model of the system order service time is established.The system order service time and equipment utilization were calculated by changing the task arrival rate,the number of cross-layer shuttles and artificial intelligence forklifts used.Then the simulation model was built by Simulink simulation platform to verify the reliability of the calculation results.In order to guide the application of improved MSS/RS,three objective functions of order service time,whole-cycle system use cost and equipment utilization rate were proposed to construct the multi-objective optimization configuration model of the system,and NSGA-II algorithm was used to solve the multi-objective optimization problem.Under the premise of satisfying the set storage volume and the scale of outbound task,the optimal configuration relation of comprehensive performance is obtained,and a set of reasonable configuration method is found out.