IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i23p3688-d1528800.html
   My bibliography  Save this article

Conceptual Framework for Adaptive Bacterial Memetic Algorithm Parameterization in Storage Location Assignment Problem

Author

Listed:
  • Kitti Udvardy

    (Multidisciplinary Doctoral School of Engineering, Széchenyi University, 9026 Győr, Hungary)

  • Polina Görbe

    (Department of Logistics and Forwarding, Széchenyi University, 9026 Győr, Hungary)

  • Tamás Bódis

    (Department of Logistics and Forwarding, Széchenyi University, 9026 Győr, Hungary)

  • János Botzheim

    (Department of Artificial Intelligence, Faculty of Informatics, ELTE Eötvös Loránd University, 1117 Budapest, Hungary)

Abstract

Recognized as an NP-hard combinatorial challenge, Storage Location Assignment Problem (SLAP) demands heuristic or algorithmic solutions for effective optimization. This paper specifically examines the enhancement of SLAP through the utilization of evolutionary algorithms, as they are particularly suitable for complex cases. Among others, the genetic algorithm (GA) is typically applied to solve this problem. This paper investigates the Bacterial Memetic Algorithm (BMA) as a possible solution for optimization. Though the comparative analysis of the BMA with the previously well-used GA algorithm under certain test parameters reveals that BMA is suitable for SLA optimization, BMA failed to achieve better results. We attribute the unsatisfactory results to the parameter settings, as illustrated by a few specific examples. However, the complexity of the problem and the parameterization does not allow for continuous manual parameter adjustment, which is why we have identified the need for a concept that automatically and adaptively adjusts the parameter settings based on the statistics and fitness values obtained during the execution. The novelty of this paper is to specify the concept of adaptive BMA parameterization and rules.

Suggested Citation

  • Kitti Udvardy & Polina Görbe & Tamás Bódis & János Botzheim, 2024. "Conceptual Framework for Adaptive Bacterial Memetic Algorithm Parameterization in Storage Location Assignment Problem," Mathematics, MDPI, vol. 12(23), pages 1-16, November.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:23:p:3688-:d:1528800
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/23/3688/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/23/3688/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Diefenbach, H. & Grosse, E.H. & Glock, C.H., 2024. "Human-and-cost-centric storage assignment optimization in picker-to-parts warehouses," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 146183, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    2. 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.
    3. 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.
    4. Boysen, Nils & de Koster, René, 2025. "50 years of warehousing research—An operations research perspective," European Journal of Operational Research, Elsevier, vol. 320(3), pages 449-464.
    5. Diefenbach, Heiko & Grosse, Eric H. & Glock, Christoph H., 2024. "Human-and-cost-centric storage assignment optimization in picker-to-parts warehouses," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1049-1068.
    6. Yuyan He & Aihu Wang & Hailiang Su & Mengyao Wang, 2019. "Particle Swarm Optimization Using Neighborhood-Based Mutation Operator and Intermediate Disturbance Strategy for Outbound Container Storage Location Assignment Problem," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-13, July.
    7. Xuming Wang & Xiaobing Yu, 2024. "Differential Evolution Algorithm with Three Mutation Operators for Global Optimization," Mathematics, MDPI, vol. 12(15), pages 1-20, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Roy, Debjit & Nigam, Shobhit & de Koster, René & Adan, Ivo & Resing, Jacques, 2019. "Robot-storage zone assignment strategies in mobile fulfillment systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 119-142.
    2. Kovács, András, 2011. "Optimizing the storage assignment in a warehouse served by milkrun logistics," International Journal of Production Economics, Elsevier, vol. 133(1), pages 312-318, September.
    3. 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.
    4. Nilendra Singh Pawar & Subir S. Rao & Gajendra K. Adil, 2024. "Improving Order-Picking Performance in E-Commerce Warehouses through Entropy-Based Hierarchical Scattering," Sustainability, MDPI, vol. 16(14), pages 1-27, July.
    5. Polten, Lukas & Emde, Simon, 2022. "Multi-shuttle crane scheduling in automated storage and retrieval systems," European Journal of Operational Research, Elsevier, vol. 302(3), pages 892-908.
    6. Thierry Sauvage & Tony Cragg & Sarrah Chraibi & Oussama El Khalil Houssaini, 2018. "Running the Machine Faster: Acceleration, Humans and Warehousing," Post-Print hal-02905068, HAL.
    7. Jiuh‐Biing Sheu & Tsan‐Ming Choi, 2023. "Can we work more safely and healthily with robot partners? A human‐friendly robot–human‐coordinated order fulfillment scheme," Production and Operations Management, Production and Operations Management Society, vol. 32(3), pages 794-812, March.
    8. Janka Saderova & Andrea Rosova & Marian Sofranko & Peter Kacmary, 2021. "Example of Warehouse System Design Based on the Principle of Logistics," Sustainability, MDPI, vol. 13(8), pages 1-16, April.
    9. 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.
    10. Jiang, Min & Huang, George Q., 2022. "Intralogistics synchronization in robotic forward-reserve warehouses for e-commerce last-mile delivery," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    11. 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.
    12. Danish Nasir & Rakesh Venkitasubramony & Suresh Kumar Jakhar, 2025. "Ergonomics in warehouse design and operations: a systematic literature review," Operational Research, Springer, vol. 25(1), pages 1-28, March.
    13. Sebastian Henn & André Scholz & Meike Stuhlmann & Gerhard Wäscher, 2015. "A New Mathematical Programming Formulation for the Single-Picker Routing Problem in a Single-Block Layout," FEMM Working Papers 150005, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    14. Pan, Jason Chao-Hsien & Shih, Po-Hsun & Wu, Ming-Hung, 2015. "Order batching in a pick-and-pass warehousing system with group genetic algorithm," Omega, Elsevier, vol. 57(PB), pages 238-248.
    15. K. L. Choy & G. T. S. Ho & C. K. H. Lee, 2017. "A RFID-based storage assignment system for enhancing the efficiency of order picking," Journal of Intelligent Manufacturing, Springer, vol. 28(1), pages 111-129, January.
    16. Jiang, Min & Leung, K.H. & Lyu, Zhongyuan & Huang, George Q., 2020. "Picking-replenishment synchronization for robotic forward-reserve warehouses," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    17. Boysen, Nils & Stephan, Konrad & Schwerdfeger, Stefan, 2024. "Order consolidation in warehouses: The loop sorter scheduling problem," European Journal of Operational Research, Elsevier, vol. 316(2), pages 459-472.
    18. Manuel Ostermeier & Andreas Holzapfel & Heinrich Kuhn & Daniel Schubert, 2022. "Integrated zone picking and vehicle routing operations with restricted intermediate storage," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(3), pages 795-832, September.
    19. Dekker, Rommert & Bloemhof, Jacqueline & Mallidis, Ioannis, 2012. "Operations Research for green logistics – An overview of aspects, issues, contributions and challenges," European Journal of Operational Research, Elsevier, vol. 219(3), pages 671-679.
    20. Atashi Khoei, Arsham & Süral, Haldun & Tural, Mustafa Kemal, 2023. "Energy minimizing order picker forklift routing problem," European Journal of Operational Research, Elsevier, vol. 307(2), pages 604-626.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:12:y:2024:i:23:p:3688-:d:1528800. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.