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Tabu Search Heuristics for the Order Batching Problem in Manual Order Picking Systems

Author

Listed:
  • Sebastian Henn

    (Faculty of Economics and Management, Otto-von-Guericke University Magdeburg)

  • Gerhard Wäscher

    (Faculty of Economics and Management, Otto-von-Guericke University Magdeburg)

Abstract

In manual order picking systems, order pickers walk or ride through a distribution warehouse in order to collect items requested by (internal or external) customers. In order to perform these operations efficiently, it is usually required that customer orders are combined into (more substantial) picking orders of limited size. The Order Batching Problem considered in this paper deals with the question of how a given set of customer orders should be combined such that the total length of all tours necessary to collect all items is minimized. For the solution of this problem the authors suggest two approaches based on the tabu search principle. The first one is a straightforward classic Tabu Search algorithm (TS), the second one is the Attribute-Based Hill Climber (ABHC). In a series of extensive numerical experiments, the newly developed approaches are benchmarked against different solution methods from literature. It is demonstrated that the proposed methods are superior to existing methods and provide solutions which may allow for operating distribution warehouses significantly more efficiently.

Suggested Citation

  • Sebastian Henn & Gerhard Wäscher, 2010. "Tabu Search Heuristics for the Order Batching Problem in Manual Order Picking Systems," FEMM Working Papers 100007, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
  • Handle: RePEc:mag:wpaper:100007
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    References listed on IDEAS

    as
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    4. Chen, Mu-Chen & Wu, Hsiao-Pin, 2005. "An association-based clustering approach to order batching considering customer demand patterns," Omega, Elsevier, vol. 33(4), pages 333-343, August.
    5. U Derigs & K Reuter, 2009. "A simple and efficient tabu search heuristic for solving the open vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(12), pages 1658-1669, December.
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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Boysen, Nils & de Koster, René & Weidinger, Felix, 2019. "Warehousing in the e-commerce era: A survey," European Journal of Operational Research, Elsevier, vol. 277(2), pages 396-411.
    2. Scholz, André & Henn, Sebastian & Stuhlmann, Meike & Wäscher, Gerhard, 2016. "A new mathematical programming formulation for the Single-Picker Routing Problem," European Journal of Operational Research, Elsevier, vol. 253(1), pages 68-84.
    3. Sören Koch & Gerhard Wäscher, 2011. "A Grouping Genetic Algorithm for the Order Batching Problem in Distribution Warehouses," FEMM Working Papers 110026, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    4. Nicolas, Lenoble & Yannick, Frein & Ramzi, Hammami, 2018. "Order batching in an automated warehouse with several vertical lift modules: Optimization and experiments with real data," European Journal of Operational Research, Elsevier, vol. 267(3), pages 958-976.
    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. A. Scholz & G. Wäscher, 2017. "Order Batching and Picker Routing in manual order picking systems: the benefits of integrated routing," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(2), pages 491-520, June.
    7. Gerhard Wäscher & André Scholz, 2015. "A Solution Approach for the Joint Order Batching and Picker Routing Problem in a Two-Block Layout," FEMM Working Papers 150004, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    8. Sandra Hahn & André Scholz, 2017. "Order Picking in Narrow-Aisle Warehouses: A Fast Approach to Minimize Waiting Times," FEMM Working Papers 170006, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    9. Sebastian Henn & Verena Schmid, 2011. "Metaheuristics for Order Batching and Sequencing in Manual Order Picking Systems," FEMM Working Papers 110011, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    10. Çağla Cergibozan & A. Serdar Tasan, 2022. "Genetic algorithm based approaches to solve the order batching problem and a case study in a distribution center," Journal of Intelligent Manufacturing, Springer, vol. 33(1), pages 137-149, January.
    11. Anderson Rogério Faia Pinto & Marcelo Seido Nagano, 2020. "Genetic algorithms applied to integration and optimization of billing and picking processes," Journal of Intelligent Manufacturing, Springer, vol. 31(3), pages 641-659, March.
    12. Sergio Gil-Borrás & Eduardo G. Pardo & Antonio Alonso-Ayuso & Abraham Duarte, 2020. "GRASP with Variable Neighborhood Descent for the online order batching problem," Journal of Global Optimization, Springer, vol. 78(2), pages 295-325, October.

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    More about this item

    Keywords

    Logistics; Warehouse Management; Order Batching; Tabu Search; Attribute-Based Hill Climber;
    All these keywords.

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