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Optimal order picker routing in the chevron warehouse

Author

Listed:
  • Makusee Masae
  • Christoph H. Glock
  • Panupong Vichitkunakorn

Abstract

Order picking has often been considered as one of the most labor- and time-intensive tasks in warehouse operations. Among the various planning problems that have to be solved in manual picker-to-parts systems, the routing of the order picker usually accounts for the highest share of the total warehouse operating cost. To minimize the cost of order picking, researchers have developed various routing procedures that guide the order picker through the warehouse to complete given customer orders. For some warehouse layouts such as the chevron warehouse, an optimal routing algorithm has not yet been proposed. This article, therefore, contributes to filling this research gap by developing an optimal order picker routing policy for the chevron warehouse. The optimal routing algorithm proposed in this article is based on the concept of graph theory and utilizes a dynamic programming procedure. In addition, we propose various simple routing heuristics for the chevron warehouse. In computational experiments, the average order picking tour lengths resulting from optimal routing and from the simple heuristics are compared. Moreover, we compare the performance of the chevron warehouse to the conventional two-block warehouse under various conditions using the tour lengths obtained by the optimal algorithms.

Suggested Citation

  • Makusee Masae & Christoph H. Glock & Panupong Vichitkunakorn, 2020. "Optimal order picker routing in the chevron warehouse," IISE Transactions, Taylor & Francis Journals, vol. 52(6), pages 665-687, June.
    • Handle: RePEc:taf:uiiexx:v:52:y:2020:i:6:p:665-687
    DOI: 10.1080/24725854.2019.1660833
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    Cited by:

    1. Saylam, Serhat & Çelik, Melih & Süral, Haldun, 2024. "Arc routing based compact formulations for picker routing in single and two block parallel aisle warehouses," European Journal of Operational Research, Elsevier, vol. 313(1), pages 225-240.
    2. 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.
    3. Tutam, Mahmut & De Koster, René, 2024. "To walk or not to walk? Designing intelligent order picking warehouses with collaborative robots," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 190(C).
    4. Çelik, Melih & Archetti, Claudia & Süral, Haldun, 2022. "Inventory routing in a warehouse: The storage replenishment routing problem," European Journal of Operational Research, Elsevier, vol. 301(3), pages 1117-1132.
    5. Vichitkunakorn, Panupong & Emde, Simon & Masae, Makusee & Glock, Christoph H. & Grosse, Eric H., 2024. "Locating charging stations and routing drones for efficient automated stocktaking," European Journal of Operational Research, Elsevier, vol. 316(3), pages 1129-1145.
    6. Mustapha Haouassi & Yannick Kergosien & Jorge E. Mendoza & Louis-Martin Rousseau, 2022. "The integrated orderline batching, batch scheduling, and picker routing problem with multiple pickers: the benefits of splitting customer orders," Flexible Services and Manufacturing Journal, Springer, vol. 34(3), pages 614-645, September.
    7. Laura Korbacher & Katrin Heßler & Stefan Irnich, 2023. "The Single Picker Routing Problem with Scattered Storage: Modeling and Evaluation of Routing and Storage Policies," Working Papers 2302, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    8. Rubio, Francisco & Llopis-Albert, Carlos & Valero, Francisco, 2021. "Multi-objective optimization of costs and energy efficiency associated with autonomous industrial processes for sustainable growth," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    9. Asghari, Mohammad & Mirzapour Al-e-hashem, S. Mohammad J., 2021. "Green vehicle routing problem: A state-of-the-art review," International Journal of Production Economics, Elsevier, vol. 231(C).
    10. Neves-Moreira, Fábio & Amorim, Pedro, 2024. "Learning efficient in-store picking strategies to reduce customer encounters in omnichannel retail," International Journal of Production Economics, Elsevier, vol. 267(C).
    11. 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.
    12. Masae, Makusee & Glock, Christoph H. & Vichitkunakorn, Panupong, 2021. "A method for efficiently routing order pickers in the leaf warehouse," International Journal of Production Economics, Elsevier, vol. 234(C).
    13. Zhang, Jiayuan & Yalcin, Mehmet G. & Hales, Douglas N., 2021. "Elements of paradoxes in supply chain management literature: A systematic literature review," International Journal of Production Economics, Elsevier, vol. 232(C).
    14. Maria A. M. Trindade & Paulo S. A. Sousa & Maria R. A. Moreira, 2022. "Ramping up a heuristic procedure for storage location assignment problem with precedence constraints," Flexible Services and Manufacturing Journal, Springer, vol. 34(3), pages 646-669, September.
    15. Jose Alejandro Cano & Pablo Cortés & Jesús Muñuzuri & Alexander Correa-Espinal, 2023. "Solving the picker routing problem in multi-block high-level storage systems using metaheuristics," Flexible Services and Manufacturing Journal, Springer, vol. 35(2), pages 376-415, June.

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