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Increasing order picking efficiency by integrating storage, batching, zone picking, and routing policy decisions

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  • van Gils, Teun
  • Ramaekers, Katrien
  • Braekers, Kris
  • Depaire, Benoît
  • Caris, An

Abstract

In order to differentiate from competitors in terms of customer service, warehouses accept late orders while providing delivery in a quick and timely way. This trend leads to a reduced time to pick an order. The main objectives of this research are to determine which order picking planning problems are related, to explain why and how individual planning problems are related, and to identify excellent performing policy combinations in several practical situations. Previous research shows contradictory findings on which planning problems are related. This paper is the first that explicitly analyzes and statistically proves the relations among storage, batching, zoning, and routing by a full factorial ANOVA. The value of combining the four main order picking planning problems is shown with a real-life case study as well as for multiple generalized warehouse designs. The results of the study clearly indicate that warehouses can achieve significant benefits by considering storage, batching, zone picking, and routing policies simultaneously. Awareness of the influence of an individual planning problem on the overall order picking performance is required to manage warehouse operations, resulting in a reduced order pick time.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:proeco:v:197:y:2018:i:c:p:243-261
    DOI: 10.1016/j.ijpe.2017.11.021
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    References listed on IDEAS

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    Cited by:

    1. Massimo Bertolini & Davide Mezzogori & Francesco Zammori, 2023. "Enhancing Manual Order Picking through a New Metaheuristic, Based on Particle Swarm Optimization," Mathematics, MDPI, vol. 11(14), pages 1-37, July.
    2. Dalia Perkumienė & Kristina Ratautaitė & Rasa Pranskūnienė, 2022. "Innovative Solutions and Challenges for the Improvement of Storage Processes," Sustainability, MDPI, vol. 14(17), pages 1-21, August.
    3. Arbex Valle, Cristiano & Beasley, John E, 2020. "Order batching using an approximation for the distance travelled by pickers," European Journal of Operational Research, Elsevier, vol. 284(2), pages 460-484.
    4. Lam, H.Y. & Ho, G.T.S. & Mo, Daniel Y. & Tang, Valerie, 2023. "Responsive pick face replenishment strategy for stock allocation to fulfil e-commerce order," International Journal of Production Economics, Elsevier, vol. 264(C).
    5. AERTS, Babiche & CORNELISSENS, Trijntje & SÖRENSEN, Kenneth, 2022. "The internal warehouse replenishment problem: the importance of storage and replenishment policies," Working Papers 2022007, University of Antwerp, Faculty of Business and Economics.
    6. Nikolaos Chondromatidis & Anastasios Gialos & Vasileios Zeimpekis, 2022. "Investigating the Performance of the Order-Picking Process by Using Smart Glasses: A Laboratory Experimental Approach," Logistics, MDPI, vol. 6(4), pages 1-26, December.
    7. MacCarthy, Bart L. & Zhang, Lina & Muyldermans, Luc, 2019. "Best Performance Frontiers for Buy-Online-Pickup-in-Store order fulfilment," International Journal of Production Economics, Elsevier, vol. 211(C), pages 251-264.
    8. Gharehgozli, Amir & Zaerpour, Nima, 2020. "Robot scheduling for pod retrieval in a robotic mobile fulfillment system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    9. Zhong, Shuya & Giannikas, Vaggelis & Merino, Jorge & McFarlane, Duncan & Cheng, Jun & Shao, Wei, 2022. "Evaluating the benefits of picking and packing planning integration in e-commerce warehouses," European Journal of Operational Research, Elsevier, vol. 301(1), pages 67-81.
    10. AERTS, Babiche & CORNELISSENS, Trijntje & SÖRENSEN, Kenneth, 2020. "Solving the joint order batching and picker routing problem, as a clustered vehicle routing problem," Working Papers 2020003, University of Antwerp, Faculty of Business and Economics.
    11. van Gils, Teun & Caris, An & Ramaekers, Katrien & Braekers, Kris, 2019. "Formulating and solving the integrated batching, routing, and picker scheduling problem in a real-life spare parts warehouse," European Journal of Operational Research, Elsevier, vol. 277(3), pages 814-830.
    12. 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).
    13. Silva, Allyson & Coelho, Leandro C. & Darvish, Maryam & Renaud, Jacques, 2020. "Integrating storage location and order picking problems in warehouse planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    14. Silva, Allyson & Roodbergen, Kees Jan & Coelho, Leandro C. & Darvish, Maryam, 2022. "Estimating optimal ABC zone sizes in manual warehouses," International Journal of Production Economics, Elsevier, vol. 252(C).
    15. 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.
    16. Liseth Contreras Hernandez & Hanser S. Jiménez G. & Priscilla P. L. Dantas & Cristiano A. V. Cavalcante, 2022. "Using multi-criteria decision making for selecting picking strategies," Operational Research, Springer, vol. 22(4), pages 3265-3290, September.

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