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Order picking in a parallel-aisle warehouse with turn penalties

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  • M. Çelik
  • H. Süral

Abstract

In many real-life routing problems, incorporating the negative effects of turns is an important, but often overlooked aspect. This is especially true for order picking in warehouses, where making the turns not only decreases the picking efficiency by reducing the speed of the vehicle, but it also results in other unquantifiable effects such as vehicle tipovers, increased congestion and increased risk of collision with pedestrians or other vehicles. In this paper, we consider the order picking problem in a parallel-aisle warehouse by taking into account the number and effect of the turns. In particular, we show that the problem of minimising the number of turns, minimising travel time under turn penalties, the biobjective problem that involves turn and travel time minimisation as separate objectives, and the triobjective problem with U-turn minimisation as a third objective can all be solved in polynomial time. Our computational results show that the algorithms we develop can generate the corresponding Pareto front very quickly, and significantly outperform heuristic approaches used in practice.

Suggested Citation

  • M. Çelik & H. Süral, 2016. "Order picking in a parallel-aisle warehouse with turn penalties," International Journal of Production Research, Taylor & Francis Journals, vol. 54(14), pages 4340-4355, July.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:14:p:4340-4355
    DOI: 10.1080/00207543.2016.1154624
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    1. Añez, J. & De La Barra, T. & Pérez, B., 1996. "Dual graph representation of transport networks," Transportation Research Part B: Methodological, Elsevier, vol. 30(3), pages 209-216, June.
    2. Nathalie Perrier & André Langevin & Ciro-Alberto Amaya, 2008. "Vehicle Routing for Urban Snow Plowing Operations," Transportation Science, INFORMS, vol. 42(1), pages 44-56, February.
    3. de Koster, Rene & Le-Duc, Tho & Roodbergen, Kees Jan, 2007. "Design and control of warehouse order picking: A literature review," European Journal of Operational Research, Elsevier, vol. 182(2), pages 481-501, October.
    4. H. Donald Ratliff & Arnon S. Rosenthal, 1983. "Order-Picking in a Rectangular Warehouse: A Solvable Case of the Traveling Salesman Problem," Operations Research, INFORMS, vol. 31(3), pages 507-521, June.
    5. Roodbergen, Kees Jan & de Koster, Rene, 2001. "Routing order pickers in a warehouse with a middle aisle," European Journal of Operational Research, Elsevier, vol. 133(1), pages 32-43, August.
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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. 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.
    3. Vidal, Thibaut & Laporte, Gilbert & Matl, Piotr, 2020. "A concise guide to existing and emerging vehicle routing problem variants," European Journal of Operational Research, Elsevier, vol. 286(2), pages 401-416.
    4. van Gils, Teun & Caris, An & Ramaekers, Katrien & Braekers, Kris & de Koster, René B.M., 2019. "Designing efficient order picking systems: The effect of real-life features on the relationship among planning problems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 47-73.
    5. 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).
    6. Rajabighamchi, Farzaneh & van Hoesel, Stan & Defryn, Christof, 2023. "Graph reduction for the planar Travelling Salesman Problem," Research Memorandum 004, Maastricht University, Graduate School of Business and Economics (GSBE).
    7. Tzu-An Chiang & Zhen-Hua Che & Chao-Wei Hung, 2023. "A K-Means Clustering and the Prim’s Minimum Spanning Tree-Based Optimal Picking-List Consolidation and Assignment Methodology for Achieving the Sustainable Warehouse Operations," Sustainability, MDPI, vol. 15(4), pages 1-15, February.
    8. Yang, Peng & Zhao, Zhijie & Guo, Huijie, 2020. "Order batch picking optimization under different storage scenarios for e-commerce warehouses," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).

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