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An exact solution approach for the order batching problem

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  • İbrahim Muter
  • Temel Öncan

Abstract

In this article, we deal with the Order Batching Problem (OBP) considering traversal, return, and midpoint routing policies. We consider the Set Partitioning Problem formulation of the OBP and develop a specially tailored column generation–based algorithm for this problem. We suggest acceleration techniques such as a column pool strategy and a relaxation of the column generation subproblem. Also, a specially devised upper-bounding procedure and a lower-bounding method based on column generation that is strengthened by adding subset-row inequalities are employed. According to the computational results, the proposed solution approach manages to solve OBP instances with up to 100 orders to optimality.

Suggested Citation

  • İbrahim Muter & Temel Öncan, 2015. "An exact solution approach for the order batching problem," IISE Transactions, Taylor & Francis Journals, vol. 47(7), pages 728-738, July.
    • Handle: RePEc:taf:uiiexx:v:47:y:2015:i:7:p:728-738
    DOI: 10.1080/0740817X.2014.991478
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    Cited by:

    1. Pardo, Eduardo G. & Gil-Borrás, Sergio & Alonso-Ayuso, Antonio & Duarte, Abraham, 2024. "Order batching problems: Taxonomy and literature review," European Journal of Operational Research, Elsevier, vol. 313(1), pages 1-24.
    2. Minfang Huang & Qiong Guo & Jing Liu & Xiaoxu Huang, 2018. "Mixed Model Assembly Line Scheduling Approach to Order Picking Problem in Online Supermarkets," Sustainability, MDPI, vol. 10(11), pages 1-16, October.
    3. Çağla Cergibozan & A. Serdar Tasan, 2019. "Order batching operations: an overview of classification, solution techniques, and future research," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 335-349, January.
    4. van Gils, Teun & Ramaekers, Katrien & Braekers, Kris & Depaire, Benoît & Caris, An, 2018. "Increasing order picking efficiency by integrating storage, batching, zone picking, and routing policy decisions," International Journal of Production Economics, Elsevier, vol. 197(C), pages 243-261.
    5. 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.
    6. Wagner, Stefan & Mönch, Lars, 2023. "A variable neighborhood search approach to solve the order batching problem with heterogeneous pick devices," European Journal of Operational Research, Elsevier, vol. 304(2), pages 461-475.
    7. Grzegorz Tarczyński, 2023. "Linear programming models for optimal workload and batching in pick-and-pass warehousing systems," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 33(3), pages 141-158.
    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).
    9. Ahmad Ebrahimi & Hyun-woo Jeon & Sang-yeop Jung, 2023. "Improving Energy Consumption and Order Tardiness in Picker-to-Part Warehouses with Electric Forklifts: A Comparison of Four Evolutionary Algorithms," Sustainability, MDPI, vol. 15(13), pages 1-28, July.
    10. Muter, İbrahim, 2020. "Exact algorithms to minimize makespan on single and parallel batch processing machines," European Journal of Operational Research, Elsevier, vol. 285(2), pages 470-483.

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