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A Discrete-Event Simheuristic for Solving a Realistic Storage Location Assignment Problem

Author

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  • Jonas F. Leon

    (Department of Computer Science, Multimedia and Telecommunication, Universitat Oberta de Catalunya, 08018 Barcelona, Spain
    Spindox España S.L., Calle Muntaner 305, 08021 Barcelona, Spain)

  • Yuda Li

    (Department of Applied Statistics and Operations Research, Universitat Politècnica de València, 03801 Alcoy, Spain)

  • Mohammad Peyman

    (Department of Computer Science, Multimedia and Telecommunication, Universitat Oberta de Catalunya, 08018 Barcelona, Spain)

  • Laura Calvet

    (Department of Telecommunication and Systems Engineering, Autonomous University of Barcelona, 08202 Sabadell, Spain)

  • Angel A. Juan

    (Department of Applied Statistics and Operations Research, Universitat Politècnica de València, 03801 Alcoy, Spain)

Abstract

In the context of increasing complexity in manufacturing and logistic systems, the combination of optimization and simulation can be considered a versatile tool for supporting managerial decision-making. An informed storage location assignment policy is key for improving warehouse operations, which play a vital role in the efficiency of supply chains. Traditional approaches in the literature to solve the storage location assignment problem present some limitations, such as excluding the stochastic variability of processes or the interaction among different warehouse activities. This work addresses those limitations by proposing a discrete-event simheuristic framework that ensures robust solutions in the face of real-life warehouse conditions. The approach followed embraces the complexity of the problem by integrating the order sequence and picking route in the solution construction and uses commercial simulation software to reduce the impact of stochastic events on the quality of the solution. The implementation of this type of novel methodology within a warehouse management system can enhance warehouse efficiency without requiring an increase in automation level. The method developed is tested under a number of computational experiments that show its convenience and point toward future lines of research.

Suggested Citation

  • Jonas F. Leon & Yuda Li & Mohammad Peyman & Laura Calvet & Angel A. Juan, 2023. "A Discrete-Event Simheuristic for Solving a Realistic Storage Location Assignment Problem," Mathematics, MDPI, vol. 11(7), pages 1-24, March.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:7:p:1577-:d:1106408
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    References listed on IDEAS

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    1. Zhang, Guoqing & Shang, Xiaoting & Alawneh, Fawzat & Yang, Yiqin & Nishi, Tatsushi, 2021. "Integrated production planning and warehouse storage assignment problem: An IoT assisted case," International Journal of Production Economics, Elsevier, vol. 234(C).
    2. Guo, Xiaolong & Chen, Ran & Du, Shaofu & Yu, Yugang, 2021. "Storage assignment for newly arrived items in forward picking areas with limited open locations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
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    4. 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).
    5. Lanza, Giacomo & Passacantando, Mauro & Scutellà, Maria Grazia, 2022. "Assigning and sequencing storage locations under a two level storage policy: Optimization model and matheuristic approaches," Omega, Elsevier, vol. 108(C).
    6. Ronald J. Mantel & Peter C. Schuur & Sunderesh S. Heragu, 2007. "Order oriented slotting: a new assignment strategy for warehouses," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 1(3), pages 301-316.
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    Cited by:

    1. Jonas F. Leon & Mohammad Peyman & Xabier A. Martin & Angel A. Juan, 2024. "Simulation of Heuristics for Automated Guided Vehicle Task Sequencing with Resource Sharing and Dynamic Queues," Mathematics, MDPI, vol. 12(2), pages 1-19, January.
    2. Mengyue Zhai & Zheng Wang, 2024. "Optimizing Rack Locations in the Mobile-Rack Picking System: A Method of Integrating Rack Heat and Relevance," Mathematics, MDPI, vol. 12(3), pages 1-20, January.

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