The Research And Application On Intelligent Warehouse Operation Key Technology

With the rapid development of computer technology, modern communications technology and automatic control technology, warehouse management level has towards information technology, automation, intelligent direction. Automatic Storage and Retrieval System(AS / RS) is an important part of modern logistics system and the AS/RS intelligent level has an important influence to the development of the whole logistics industry. The higher the intelligence, the more marked the logistics industry developed. As an important part of the AS/RS management, the goods allocation of Warehouse management issue has been a very difficult problem and slotting optimization is an important part of the job optimization. Without any increase in investment and equipment, it can reduce the operation time and greatly improve the efficiency of the warehouse, therefore, the study of this problem is of high practical significance and theoretical value.This paper researches the balanced optimization problem about Multi roadway homework with Genetic Algorithm(GA) and Binary Particle Swarm Optimization(BPSO). The main research work includes the following several aspects:(1) This paper studies the role of entry-item-quantity(EIQ) in warehouse management and based on the EIQ analysis about the daily storage capacity of related enterprises, this paper presents a reservoir area optimization approach based on the EIQ analysis about Automatic Storage and Retrieval System.(2) This paper studies the roadway homework balance optimization problem. In order to optimize the ratio of the distance which each stacker is running in its roadway, this paper established a balanced optimization model about roadway operation based on the constraint condition of item constraint domain. For the established model, this paper designed a parent hybrid genetic algorithm and through a lot of testing operations in Matlab environment such as high-volume warehousing operations, low-volume warehousing operations, verify the algorithm can effectively solve the balance optimization problem of Multi roadway.(3) For the high-volume warehousing operations, this paper carried out performance comparison experiments with parents hybrid genetic algorithm and binary particle swarm optimization algorithm and the comparison of the results prove that the optimization effect of parents hybrid genetic algorithm is better than binary particle swarm optimization algorithm, and verifying that the parents hybrid genetic algorithm is more suitable to solve the Multi roadway balance optimization problems.(4) The binary particle swarm optimization and parents hybrid genetic algorithm which this paper studied have been applied in the Warehouse Management System(WMS) software of related enterprises and the operating results is good.