IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v29y2018i6d10.1007_s10845-015-1177-7.html
   My bibliography  Save this article

Multi-objective optimization of electronic product goods location assignment in stereoscopic warehouse based on adaptive genetic algorithm

Author

Listed:
  • Bo Yan

    (South China University of Technology)

  • Chang Yan

    (South China University of Technology)

  • Feng Long

    (South China University of Technology)

  • Xing-Chao Tan

    (South China University of Technology)

Abstract

Storage is an important part of commodity circulation. A certain amount of material must be stored to meet the needs of social production and consumption within a certain time to maintain the smooth process of social reproduction. This study focuses on warehousing optimization and goods location assignment when electronic products are stored in a stereoscopic storehouse. Moreover, this study is based on a theoretical study on genetic algorithm. On the basis of the background of the current warehouse management and cargo distribution of LCM module products warehouse belonging to W company, this study uses the dynamic goods location assignment strategy of stochastic inventory, and builds a multi-objective goods location assignment model of a stereoscopic warehouse. To simplify the calculations and improve the efficiency, we conduct a Matlab simulation on the basis of practical data by adopting a modified genetic operator and converting multi-objective optimization by the changing weight coefficient. The adaptive genetic algorithm can be used to make a multi-objective goods location assignment model that efficiently converges to the optimal solution.

Suggested Citation

  • Bo Yan & Chang Yan & Feng Long & Xing-Chao Tan, 2018. "Multi-objective optimization of electronic product goods location assignment in stereoscopic warehouse based on adaptive genetic algorithm," Journal of Intelligent Manufacturing, Springer, vol. 29(6), pages 1273-1285, August.
    • Handle: RePEc:spr:joinma:v:29:y:2018:i:6:d:10.1007_s10845-015-1177-7
    DOI: 10.1007/s10845-015-1177-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-015-1177-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-015-1177-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Cardona, Luis F. & Soto, Diego F. & Rivera, Leonardo & Martínez, Hector J., 2015. "Detailed design of fishbone warehouse layouts with vertical travel," International Journal of Production Economics, Elsevier, vol. 170(PC), pages 825-837.
    2. Muppani (Muppant), Venkata Reddy & Adil, Gajendra Kumar, 2008. "Efficient formation of storage classes for warehouse storage location assignment: A simulated annealing approach," Omega, Elsevier, vol. 36(4), pages 609-618, August.
    3. Gu, Jinxiang & Goetschalckx, Marc & McGinnis, Leon F., 2010. "Research on warehouse design and performance evaluation: A comprehensive review," European Journal of Operational Research, Elsevier, vol. 203(3), pages 539-549, June.
    4. Lim, Ming K. & Bahr, Witold & Leung, Stephen C.H., 2013. "RFID in the warehouse: A literature analysis (1995–2010) of its applications, benefits, challenges and future trends," International Journal of Production Economics, Elsevier, vol. 145(1), pages 409-430.
    5. Yao, Can-Zhong & Lin, Ji-Nan & Liu, Xiao-Feng & Zheng, Xu-Zhou, 2014. "Dynamic features analysis for the large-scale logistics system warehouse-out operation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 31-42.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. Huifang Li & Yin Wang, 2023. "Hierarchical Multimodal Hub Location Problem with Carbon Emissions," Sustainability, MDPI, vol. 15(3), pages 1-23, January.
    3. Jingran Liang & Zhengning Wu & Chenye Zhu & Zhi-Hai Zhang, 2022. "An estimation distribution algorithm for wave-picking warehouse management," Journal of Intelligent Manufacturing, Springer, vol. 33(4), pages 929-942, April.
    4. Zheng Wang & Wei Xu & Xiangpei Hu & Yong Wang, 2022. "Inventory allocation to robotic mobile-rack and picker-to-part warehouses at minimum order-splitting and replenishment costs," Annals of Operations Research, Springer, vol. 316(1), pages 467-491, September.
    5. 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.

    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. 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. Derhami, Shahab & Smith, Jeffrey S. & Gue, Kevin R., 2020. "A simulation-based optimization approach to design optimal layouts for block stacking warehouses," International Journal of Production Economics, Elsevier, vol. 223(C).
    3. Zhang, Guoqing & Nishi, Tatsushi & Turner, Sarina D.O. & Oga, Keisuke & Li, Xindan, 2017. "An integrated strategy for a production planning and warehouse layout problem: Modeling and solution approaches," Omega, Elsevier, vol. 68(C), pages 85-94.
    4. Chen, Gang & Feng, Haolin & Luo, Kaiyi & Tang, Yanli, 2021. "Retrieval-oriented storage relocation optimization of an automated storage and retrieval system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
    5. Ivan Derpich & Juan M. Sepúlveda & Rodrigo Barraza & Fernanda Castro, 2022. "Warehouse Optimization: Energy Efficient Layout and Design," Mathematics, MDPI, vol. 10(10), pages 1-17, May.
    6. Syam, Siddhartha S. & Côté, Murray J., 2010. "A location-allocation model for service providers with application to not-for-profit health care organizations," Omega, Elsevier, vol. 38(3-4), pages 157-166, June.
    7. 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.
    8. Correia, Isabel & Melo, Teresa & Saldanha-da-Gama, Francisco, 2012. "Comparing classical performance measures for a multi-period, two-echelon supply chain network design problem with sizing decisions," Technical Reports on Logistics of the Saarland Business School 1, Saarland University of Applied Sciences (htw saar), Saarland Business School.
    9. Thierry Sauvage & Tony Cragg & Sarrah Chraibi & Oussama El Khalil Houssaini, 2018. "Running the Machine Faster: Acceleration, Humans and Warehousing," Post-Print hal-02905068, HAL.
    10. Overholts II, Dale L. & Bell, John E. & Arostegui, Marvin A., 2009. "A location analysis approach for military maintenance scheduling with geographically dispersed service areas," Omega, Elsevier, vol. 37(4), pages 838-852, August.
    11. 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.
    12. Ene, Seval & Küçükoğlu, İlker & Aksoy, Aslı & Öztürk, Nursel, 2016. "A genetic algorithm for minimizing energy consumption in warehouses," Energy, Elsevier, vol. 114(C), pages 973-980.
    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. Bortolini, Marco & Faccio, Maurizio & Ferrari, Emilio & Gamberi, Mauro & Pilati, Francesco, 2017. "Time and energy optimal unit-load assignment for automatic S/R warehouses," International Journal of Production Economics, Elsevier, vol. 190(C), pages 133-145.
    15. 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.
    16. Shi, Ye & Yu, Yugang & Dong, Yuxuan, 2021. "Warehousing platform’s revenue management: A dynamic model of coordinating space allocation for self-use and rent," European Journal of Operational Research, Elsevier, vol. 293(1), pages 167-176.
    17. Yao, Can-Zhong & Lin, Ji-Nan & Zheng, Xu-Zhou & Liu, Xiao-Feng, 2015. "The study of RMB exchange rate complex networks based on fluctuation mode," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 359-376.
    18. Maniezzo, Vittorio & Boschetti, Marco A. & Gutjahr, Walter J., 2021. "Stochastic premarshalling of block stacking warehouses," Omega, Elsevier, vol. 102(C).
    19. 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.
    20. Zhuang, Yanling & Zhou, Yun & Hassini, Elkafi & Yuan, Yufei & Hu, Xiangpei, 2024. "Improving order picking efficiency through storage assignment optimization in robotic mobile fulfillment systems," European Journal of Operational Research, Elsevier, vol. 316(2), pages 718-732.

    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:spr:joinma:v:29:y:2018:i:6:d:10.1007_s10845-015-1177-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.