• IE interfaces
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• v.15 no.4
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• pp.382-390
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• 2002

This paper deals with planning of order-picking warehouse considering the batch order picking for transportation equipments to pick consumers' orders at a time among order-picking methods and a systematic approach method in order to analyze the order-picking warehouse which can perform optimal operation. To estimate an operating time of transportation equipments to carry out order-picking, this paper suggests three operations : first, to design the refrigerated warehouse using warehouse design parameters, second, to calculate the travel time of transporters considering four types of times with the probabilistic picking frequency, and third, to analyze an order-picking warehouse to construct a simulation model with the AutoMod as a simulation tool. We apply this model to a refrigerated warehouse company in Busan.

• Journal of Navigation and Port Research
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• v.33 no.7
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• pp.477-482
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• 2009

In this paper the order picking problem in warehouses is considered, a topic which has received considerable attention from the international academic body in recent years. The order picking problem deals with the retrieval of order items from prespecified locations in the warehouse, and its objective is usually the minimization of travel time or travel distance. Hence, a well-thought order picking policy in combination with an appropriate storage policy will enhance warehouse efficiency and reduce operational costs. This paper starts with a literature overview summarizing approaches to routing order pickers, assigning stock-keeping units to pick locations and designing warehouse layouts. Since the layout design might affect both storage and routing policies, the three factors are interdependent with respect to order picking performance. To test these interdependencies, a simulation experiment was set up, involving two types of warehouse layout, four types of storage policy, five well-known heuristics and five sizes of order picking list. Our results illustrate that from the point of view of order picking distance minimization it is recommended to equip the warehouse with a third cross aisle, although this comes at the cost of a certain space loss. Additionally, we propose a set of most appropriate matches between order picking heuristics and storage policies. Finally, we give some directions for further research and recommend an integrated approach involving all factors that affect warehouse efficiency.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1035-1041
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• 2003

Recent studies among various activities taking place in order-picking warehouse system have shown various researches to reduce the order-picking costs occupying more than half the total costs. One way of improving the warehouse system performance is to separate from a picking area and a reserve area in one unit rack. This study is concerned on the performance evaluation model for picking and replenishing facility of refrigerated warehouse using simulation method. In this study, we developed a mathematical model to compute the system performance solve this problem using simulation method. We demonstrate the system performance using AutoMod Simulator and verify the results to compare mathematical results of the system performance of warehouse system. A systematic approach proposed n this study for an optimal planning of order-picking warehouse is known as an effective method for planning of order-picking warehouse and a performance evaluation problem considering both picking and replenishment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.2
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• pp.17-24
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• 2013

This paper is to analyze the picking lead time for picking batch size in a warehouse system and to get minimum picking batch size that is the warehouse system feasible. The warehouse system consists of aisles and racks, which two racks face each other through aisle. The products are picked from the storage locations by batch size. The probability that items are picked in the each row of the rack in the aisle for order picking activity is derived. The picking lead time for picking batch size is the time passed from the first picking location to arrival at starting location in aisle picking all items included in a batch size. The picking lead time for picking batch size in an aisle is analyzed. The picking lead time for picking batch size in the whole warehouse system is obtained. The warehouse system is feasible if all items that customers order are picked from the storage locations for same period. The picking batch size that is the warehouse system feasible is obtained. The problem is analyzed, a solution procedure is developed, and a numerical example is shown to explain the problem.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.4
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• pp.1-10
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• 2011

This paper addresses the analysis of the travel distance and order picking time of the vehicle in a aisle when items are picked by the batch in a warehouse system. Batching is to combine several orders in a single tour of the storage/retrieval machine. An advantage of batching is that the length of a tour for a batch of orders is shorter than the sum of the individual orders' tour lengths. The average travel distance and order picking time when a batch is picked in a aisle of the warehouse systems are analyzed for the batch size. And when the vehicle is idle, the dwell point of the vehicle to minimize to the response distance is analyzed. As the batch size is increased, average order picking time per item is decreased. The problem is analyzed and a numerical example is showed to explain the problem.

• IE interfaces
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• v.16 no.spc
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• pp.105-110
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• 2003

This paper deals with a performance evaluation model of transporters in refrigerate warehouse. This study focussed on determining refrigerate warehouse design to minimize the expected travel time to improve the transporter performance and to minimize the operating costs. This study proposes the important detail aspects of refrigerate warehouse design, operational parameters and congestions. For solving this problem, we have shown a mathematical model to compute the initial value of the system performance and also a simulation model using AutoMod. A systematic approach proposed in this study for an optimal planning of order-picking warehouse is known as an effective method for the planning of order-picking warehouse and a performance evaluation problem of refrigerate warehouse operation.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.4
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• pp.271-278
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• 2011

This paper is to review and organize performance strategies, issues, and measures for the efficient operation of order picking function. Order picking is the process of retrieving items from storage to meet a specific customer order, which is known to be the most labor-intensive and costly function among all the warehouse functions. This function is also important in that it has a critical impact on downstream customer service. For understanding the background of order picking and related performance issues, we will briefly introduce warehousing functions. Then we will introduce material handling within a warehouse and order picking strategies. Lastly, we will discuss about performance issues and measures in the domain of order picking operations. Productive and quality measures will be reviewed in more detail.

• Journal of the Korea Society of Computer and Information
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• v.8 no.4
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• pp.159-164
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• 2003

Location of stock in a warehouse directly affects the total materials handling expense of all goods moving through the warehouse. The purpose of this paper is to develop a storage policy in order picking warehouse, the block-based storage policy to minimize the total order picking time. In block-based storage policy, the rack is divided into blocks and items are assigned to each block based on the turn-over rate of each item and the average distance between the blocks and the dock. To demonstrate the performance of the proposed policy, we compare with the existing method called class-based storage policy under various matching methods.

• Journal of Information Technology Applications and Management
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• v.18 no.1
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• pp.125-141
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• 2011

As the sales volume of online shops increases, the job burden in the back-offices of the online shops also increases. Order picking is the most labor-intensive operation among the jobs in a back-office and mid-size pure click online shops are experiencing the time delay and complexity in order picking nowadays while fulfilling their customers' orders. Those warehouses of the mid-size shops are based on manual systems, and as order pickings are repeated, the warehouses get a mess and lots of products in those warehouses are getting missing, which results in severe delay in order picking. To overcome this kind of problem in online clothing shops, we research a methodology to locate warehousing products. When products arrive at a warehouse, they are packed into a box and located on a rack in the warehouse. At this point, the operator should determine the box to be put in and the location on the rack for the box to be put on. This problem could be formulated as an Integer Programming model, but the branch-and bound algorithm to solve the IP model requires enormous computation, and sometimes it is even impossible to get a solution in a proper time. So, we relaxed the problem, developed a set of heuristics as a methodology to get a semi-optimum in an acceptable time, and proved by an experiment that the solutions by our methodology are satisfactory and acceptable by field managers.

• Journal of the Korea Society for Simulation
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• v.28 no.1
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• pp.1-9
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• 2019

Recently, as the importance of warehouses has increased, much efforts are being made to improve the picking process in order to cope with a small amount of high frequency and fast delivery. This study proposes an algorithm to assign orders to pickers in the situation where Single Order Picking policy is used. This algorithm utilizes five attributes related to picking such as picking processing time, elapsed time after receipt of order, inspection/packing workstation situation, picker error, customer importance. A measure of urgency is introduced so that the units of measure for each attribute are the same. The higher the urgency, the higher the allocation priority. In the proposed algorithm, the allocation policy can be flexibly adjusted according to the operational goal of the picking system by changing the weight of each attribute. Simulation experiments were performed on a hypothetical small logistics warehouse. The results showed excellent performance in terms of system throughput and flow time.