Study On Operational Policies Optimization In Automated Storage/Retrieval Warehousing System

Warehouses are an important part of supply chain system and play a crucial role in storing and transporting units.With the diversification of customers and commodities in the e-commerce industry,the storage capacity and operation efficiency of warehousing system are required to be higher.And the efficiency of warehousing system directly affects the performance of the whole supply chain.There are many factors that affect the efficiency of warehousing system,such as Warehousing System Selection,Warehousing System Design,Storage policies input/output point policies,dwell-point policies.This paper focuses the impact of input/output point policies and storage policies on the operational efficiency of warehousing system.First,the dissertation considers the optimization problems in the 3D AS/RS with two merged Input and Output point policies.While previous studies put the input and Output point together at the lower left corner or the lower mid-point of the storage rack.This thesis builds the expected travel time models considering two merged Input and Output point policies: input and output points elevated at one side,input and output points elevated at the midpoint.We theoretically find the optimal system structure and use simulation for validation.Then we compare two I/O point policies in terms of expected S/R machine travel time.The results show that the mid-point elevation is better in the two merged I/O point policies and outperforms the I/O point at the lower mid-point by about 6.07% in terms of the expected travel time.Then,the optimization problems of two separate input/output point policies in 3D AS/RS are studied.The relevant research literature of this system assumes that the input and output points are located in the same place.This paper innovatively considers when the input point and the output point are located at two different places.And we consider two separate input/output point policies: input and output points at opposite ends of the aisle,the I/O points at the same end of the aisle but at different elevations.The dissertation presents a continuous expected travel time models of the storage and retrieval machine and validates the accuracy of the travel time models by computer simulations.The optimal system structure is obtained by convex optimization method.The comparative analysis results of the two I/O point policies show that the 3D AS/RS is more efficient when the input and output points are located at the same end of the aisle but at different elevations.Finally,the optimization of efficiency of multi-deep automated storage and retrieval system under class-based storage policies is studied.Previous studies on storage policies mainly focus on single-deep,double-deep and three-dimensional automated storage and retrieval system,while class-based storage policies have not been studied in multi-deep automated storage and retrieval system.This paper constructs the expected retrieval time model of the crane under three different storage policies.The three storage policies are random storage policy,class-based storage policy on picking face,class-based storage policy on both picking face and depth direction of the rack.The formulation of the optimal system size is derived by minimizing the expected travel time model of the S/R machine.Then,compared with the simulation model and the theoretical model,the maximum relative error of the two models is 4.3%.Finally,a large number of numerical experiments are carried out to compare and analyze the performance of these storage policies.The results show that class-based storage policy always outperform the random storage policy in terms of expected travel time,and the class-based storage policy that zoning on both picking face and the depth direction may not be better than that only zoning on the picking face,while it may be harder to handle in the system.