Optimization Method Of Picking Path Problem In The Multi-block Warehouse

With the globalization of economy and the rapid development of e-commerce,enterprises have put forward higher and higher requirements for logistics systems.How to reduce logistics costs effectively has become the focus of the enterprises under the premise of ensuring high-quality logistics service level.This problem is especially important to third-party warehouse centers which focus on providing specialized and high-quality service.Its operations mainly includes receiving,loading,in-library management,billing,picking,packaging,and distribution.And picking is the core link,whose labor cost and time cost are both account for about 60% of the total cost of the warehouse center operation.Therefore,the order picking efficiency directly affects the overall working efficiency of the warehouse center,and optimizing the length of the picking path is effective on it.This paper takes a multi-block warehouse as the research object,and systematically studies the optimization of warehouse picking path.Firstly,this paper clarifies the research content,methods and innovation points in the context of summarizing the research results about warehouse picking path at home and abroad.Then it expounds the related basic theories and methods involved in this paper,including the concept,structure,operation flow and picking path optimization problem of the warehouse center.Secondly,it analyzes the picking path current situation and existing problems of the storage center in Company A,such as single picking method and long picking path.In view of the problem that the personnel safety and high damage rate cannot be guaranteed due to the single picking method,this paper divides the picking method of multi-block warehouse into single vehicle and multivehicle for an order.In view of the problem that low picking efficiency caused by the long picking path,this paper establishes a path optimization model with two picking methods and uses the artificial fish swarm algorithm(AFSA)to solve the problem.Through analyzing a lot of experimental data during the solution process,it is found that the number of goods to be picked has a certain relationship with the parameters of AFSA.Based on this,the parameters are set to optimize the solution of the problem.Finally,the picking path solved by AFSA is compared with the one solved by “U+Return” strategy which adopted by Company A in the real world.And the picking path with single vehicle based on the artificial fish swarm algorithm is compared with the multi-vehicle in the same time.The result of experiment indicates that the proposed method is strongly effective and practicable,and provides a certain reference value for logistics enterprises to improve the efficiency of picking and the safety of personnel.