• Journal of the Korea Society for Simulation
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• v.20 no.2
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• pp.67-76
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• 2011

Order picking in automotive service parts warehouses is considered to be the most labor-intensive operation. Such warehouses contain hundreds of thousands of items, but normally 20% of products contribute to about 80% of turnover according to Pareto's 80-20 principle. Therefore most fast moving items are located near an outbound area which is called the "Golden Zone". Order picking routing efficiency is related to productivity and labor cost. However, most companies use simple methods. In this paper, we describe a series of computational experiments over a set of test cases where, we compared various previously existing routing heuristics to an optimal algorithm. We focus on examining the influence of the golden zone on the performance and selection of routing methods. The results obtained show that the optimal routing method increases the productivity at least 17.2%, and all the routing methods have better performance as the pick up rate from the golden zone increases.

• The Journal of Bigdata
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• v.2 no.1
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• pp.49-58
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• 2017

The inventory location is the mos important factor which decide the efficiency of picking orders. According to the inventory location, it is possible to optimize the route for picking order, and then it makes us to expect the cost reduction and efficiency improvement. However, it is practical situation to make decisions where to keep the products based on manager's intuition and experience, not based on the systematical or analytical approach. In this research, with the practical order data of cropper product and layout for the storage yard, the association rules have found, and then the new methodology has been devised to make the decision where to keep the inventory. By utilizing the practical order data for a year, it has been proved that the proposed approach can reduce the total distance of the all routes for picking order and solve the problem of delayed delivery.

• Journal of Biosystems Engineering
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• v.33 no.1
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• pp.51-57
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• 2008

The purpose of this study was to develop an optimal path planning program for autonomous speed sprayer in orchard. A digital map which contained coordinate information and entity information including height, width, radius of main stem, and disease of a trees was developed to build an optimal path. The digital map, dynamic programming and order-picking algorithm were used for planning an optimal path for autonomous speed sprayers. When this algorithm applied to rectangular-shaped orchards to travel whole trees, the developed program planned the same working path and same traveling distance as those of created by conventional method. But for irregular-shaped orchards, developed program planned differently and 5.06% shorter path than conventional method. When applied to create path for multi-selected trees, irregular-shaped orchards showed 13.9% shorter path and also rectangular-shaped orchards showed 9.1% shorter path. The developed program always planned shorter path than the path created by conventional method despite of variation of shape of orchards.