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Order Picking Problem: A Model for the Joint Optimisation of Order Batching, Batch Assignment Sequencing, and Picking Routing

Author

Listed:
  • Antonio Maria Coruzzolo

    (Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, Via Amendola 2, 42122 Reggio Emilia, Italy)

  • Francesco Lolli

    (Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, Via Amendola 2, 42122 Reggio Emilia, Italy)

  • Elia Balugani

    (Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, Via Amendola 2, 42122 Reggio Emilia, Italy)

  • Elisa Magnani

    (Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, Via Amendola 2, 42122 Reggio Emilia, Italy)

  • Miguel Afonso Sellitto

    (Production and Systems Graduate Program, University of Vale do Rio dos Sinos, Avenida Unisinos 950, São Leopoldo 93022-180, Brazil)

Abstract

Background: Order picking is a critical activity in end-product warehouses, particularly using the picker-to-part system, entail substantial manual labor, representing approximately 60% of warehouse work. Methods: This study develops a new linear model to perform batching, which allows for defining, assigning, and sequencing batches and determining the best routing strategy. Its goal is to minimise the completion time and the weighted sum of tardiness and earliness of orders. We developed a second linear model without the constraints related to the picking routing to reduce complexity. This model searches for the best routing using the closest neighbour approach. As both models were too complex to test, the earliest due date constructive heuristic algorithm was developed. To improve the solution, we implemented various algorithms, from multi-start with random ordering to more complex like iterated local search. Results: The proposed models were tested on a real case study where the picking time was reduced by 57% compared to single-order strategy. Conclusions: The results showed that the iterated local search multiple perturbation algorithms could successfully identify the minimum solution and significantly improve the solution initially obtained with the heuristic earliest due date algorithm.

Suggested Citation

  • Antonio Maria Coruzzolo & Francesco Lolli & Elia Balugani & Elisa Magnani & Miguel Afonso Sellitto, 2023. "Order Picking Problem: A Model for the Joint Optimisation of Order Batching, Batch Assignment Sequencing, and Picking Routing," Logistics, MDPI, vol. 7(3), pages 1-18, September.
    • Handle: RePEc:gam:jlogis:v:7:y:2023:i:3:p:61-:d:1237166
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    References listed on IDEAS

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    1. Jianzhong Du & Joseph Y.-T. Leung, 1990. "Minimizing Total Tardiness on One Machine is NP-Hard," Mathematics of Operations Research, INFORMS, vol. 15(3), pages 483-495, August.
    2. Chen, Tzu-Li & Cheng, Chen-Yang & Chen, Yin-Yann & Chan, Li-Kai, 2015. "An efficient hybrid algorithm for integrated order batching, sequencing and routing problem," International Journal of Production Economics, Elsevier, vol. 159(C), pages 158-167.
    3. 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.
    4. 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.
    5. Matusiak, Marek & de Koster, René & Saarinen, Jari, 2017. "Utilizing individual picker skills to improve order batching in a warehouse," European Journal of Operational Research, Elsevier, vol. 263(3), pages 888-899.
    6. Jing-Sheng Song & Geert-Jan van Houtum & Jan A. Van Mieghem, 2020. "Capacity and Inventory Management: Review, Trends, and Projections," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 36-46, January.
    7. Francesco Lolli & Francesco Lodi & Claudio Giberti & Antonio Maria Coruzzolo & Samuele Marinello & Muhammet Gul, 2022. "Order Picking Systems: A Queue Model for Dimensioning the Storage Capacity, the Crew of Pickers, and the AGV Fleet," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-15, February.
    8. Lu, Wenrong & McFarlane, Duncan & Giannikas, Vaggelis & Zhang, Quan, 2016. "An algorithm for dynamic order-picking in warehouse operations," European Journal of Operational Research, Elsevier, vol. 248(1), pages 107-122.
    9. Valle, Cristiano Arbex & Beasley, John E. & da Cunha, Alexandre Salles, 2017. "Optimally solving the joint order batching and picker routing problem," European Journal of Operational Research, Elsevier, vol. 262(3), pages 817-834.
    10. 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.
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