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Selection of manual order picking concepts in a warehouse by means of simulation tools

100%
Jakubiak M., Tarczyński G.
Mathematical Economics
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2012
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issue 8 (15)
45-62
EN
Along with the lengthening of a product’s path from a producer to a customer, and with speeding up the flow of goods, information and finance in the chain of supply, the places where these flows and streams could be regulated are required. The control over the flow of material and non-material goods and the increase of the supply chain’s effectiveness are possible thanks to the units called logistic hubs, which are mainly represented by a warehouse. In this paper, the authors analyze the influence of the three most popular strategies of warehouse worker’s movements through the warehouse on order picking time. The simulation was carried out on the example of a real distribution warehouse which is owned by one of the leading discount stores networks in Poland. In the research, a special computer software, written for the purpose of the research, was used. This software enables matching the best order picking concept to the conditions of a given enterprise.
2
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The influence of order picking zone’s configuration on the time of the order picking process

100%
Jakubiak M.
Econometrics. Ekonometria. Advances in Applied Data Analytics
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2014
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issue 3(45)
138-150
EN
The pressure connected with cost cutting parallel to an increase in consumer service quality as well as speeding up the flow of goods are the result of a worldwide economy trend connected with big competition in the market. That is why in modern economy even small movements of goods at short distances are becoming more and more important. The order picking problems in a warehouse are an important aspect in improving the productivity of modern logistic hubs. According to various estimates, the costs associated with order picking in a warehouse are from 55 to 65% of the total material handling costs. The author, using simulation tools, examines the influence of order picking zone’s configuration on the time of the order picking process. By means of the implemented simulation methods, it is possible to match the appropriate order picking process to the needs of a given enterprise.
3
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Analytical and simulation determination of order picking time in a low storage warehouse for shared storage systems

100%
DMYTRÓW K.
Operations Research and Decisions
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2022
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vol. 32
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issue 2
34-51
EN
The aim of the research is comparison between average order picking times obtained using the analytical model and simulation methods for shared storage systems. We also compare the results obtained with the results obtained for dedicated storage. We assume the random and ABC-class storage (with within and across aisle storage policies). We select the locations by means of the TOPSIS method for two take-out strategies: quantity adjustment (QA) and priority of partial units (PPU). We determine the route by using s-shape and return heuristics. In most cases, the simulated average order picking times are shorter than the analytical ones. It results from not considering the criteria’ weights in calculation of the analytical order picking time. Also, the results for shared storage with QA strategy are in most cases better than for dedicated storage. This might imply an advantage of shared over dedicated storage, but needs further confirmation.
4
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Analysis of the impact of storage parameters and the size of orders on the choice of the method for routing order picking

100%
TARCZYŃSKI G.
Operations Research and Decisions
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2012
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vol. 22
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issue 4
105-120
EN
The paper presents an analysis of the impact of the number of picking aisles, slots in a rack, the size of pick lists, and the routing method on the performance of the order picking process. In the analysis, the forklift truck’s maneuvers such as turns back and turns aside, omitted by some scientists, are considered. Although only random storage assignment is examined in this paper, the possible congestion effect is considered. Experiments were performed by the use of simulations.
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