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Performance Analysis of Picking Path Strategies in Chevron Layout Warehouse

Author

Listed:
  • Huwei Liu

    (School of Management and Engineering, Capital University of Economics and Business, Beijing 100070, China
    School of Information, Beijing Wuzi University, Beijing 101149, China)

  • Fan Wang

    (School of Information, Beijing Wuzi University, Beijing 101149, China)

  • Junhui Zhao

    (School of Information, Beijing Wuzi University, Beijing 101149, China)

  • Jianglong Yang

    (School of Management and Engineering, Capital University of Economics and Business, Beijing 100070, China
    School of Information, Beijing Wuzi University, Beijing 101149, China)

  • Chunqiao Tan

    (School of Business, Nanjing Audit University, Nanjing 211815, China)

  • Li Zhou

    (School of Information, Beijing Wuzi University, Beijing 101149, China)

Abstract

Order picking is the part with the highest proportion of operation cost and time in the warehouse. The characteristics of small-batch and multi-frequency current orders reduce the applicability of the traditional layout in the warehouse. Besides this, the improvement of the layout will also affect the picking path, such as the Chevron warehouse layout, and at present, there is a lack of research on order picking with multiple picking locations under non-traditional layouts. In order to minimize the order picking cost and time, and expand the research in this field, this paper selects the Chevron layout to design and describe the warehouse layout, constructs the picking walking distance model of Return-type, S-type and Mixed-type path strategies in the random storage Chevron layout warehouse, and uses the Cuckoo Search (CS) algorithm to solve the picking walking distance generated by the Mixed-type path. Compared with the existing single-command order picking research, the order picking problem of multi picking locations is more suitable for the reality of e-commerce warehouses. Moreover, numerical experiments are carried out on the above three path strategies to study the impact of different walking paths on the picking walking distance, and the performance of different path strategies is evaluated by comparing the order picking walking distance with the different number of locations to be picked. The results show that, among the three path strategies, the Mixed-type path strategy is better than the Return-type path strategy, and the average optimization proportion is higher than 20%. When the number of locations to be picked is less than 36, the Mixed-type path is better than the S-type path. With the increase of the number of locations to be picked, the Mixed-type path is gradually worse than the S-type path. When the number of locations to be picked is less than 5, the Return-type path is better than the S-type path. With the increase of the number of locations to be picked in the order, the S-type path is gradually better than the Return-type path.

Suggested Citation

  • Huwei Liu & Fan Wang & Junhui Zhao & Jianglong Yang & Chunqiao Tan & Li Zhou, 2022. "Performance Analysis of Picking Path Strategies in Chevron Layout Warehouse," Mathematics, MDPI, vol. 10(3), pages 1-18, January.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:3:p:395-:d:735495
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    Citations

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    Cited by:

    1. Li Zhou & Huwei Liu & Junhui Zhao & Fan Wang & Jianglong Yang, 2022. "Performance Analysis of Picking Routing Strategies in the Leaf Layout Warehouse," Mathematics, MDPI, vol. 10(17), pages 1-28, September.
    2. Shandong Mou, 2022. "Integrated Order Picking and Multi-Skilled Picker Scheduling in Omni-Channel Retail Stores," Mathematics, MDPI, vol. 10(9), pages 1-19, April.
    3. Kaibo Liang & Li Zhou & Jianglong Yang & Huwei Liu & Yakun Li & Fengmei Jing & Man Shan & Jin Yang, 2023. "Research on a Dynamic Task Update Assignment Strategy Based on a “Parts to Picker” Picking System," Mathematics, MDPI, vol. 11(7), pages 1-29, March.
    4. Dragan Djurdjević & Nenad Bjelić & Dražen Popović & Milan Andrejić, 2022. "A Combined Dynamic Programming and Simulation Approach to the Sizing of the Low-Level Order-Picking Area," Mathematics, MDPI, vol. 10(20), pages 1-23, October.

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