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Performance Analysis of Three Intelligent Algorithms on Route Selection of Fishbone Layout

Author

Listed:
  • Li Zhou

    (School of Information, Beijing Wuzi University, Beijing 101149, China)

  • Zhaochan Li

    (School of Information, Beijing Wuzi University, Beijing 101149, China)

  • Ning Shi

    (School of Information, Beijing Wuzi University, Beijing 101149, China)

  • Shaohua Liu

    (School of Information, Beijing Wuzi University, Beijing 101149, China)

  • Ke Xiong

    (School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China)

Abstract

The Internet of Things (IoT) has become an important strategy in the current round of global economic growth and technological development and provides a new path for the intelligent development of the logistics industry. With the development of the economy, the demand for logistics benefits is becoming more important. The appropriate use of technologies related to IoT to improve logistics efficiency, such as cloud computing, mobile computing and data mining, has become a topic of considerable research interest. Picking operations are currently an extremely important and cumbersome aspect of logistics center tasks. To shorten the picking distance and improve work efficiency, this paper uses the genetic algorithm, ant colony algorithm and cuckoo algorithm to optimize the picking path in a fishbone-layout warehouse and establishes an optimized model of the warehouse picking path under the fishbone layout. Data-mining technology is used to simulate the model and obtain the simulation data under the condition of multiple orders. The results provide a theoretical basis for the study of the fishbone-layout picking path model and has certain practical significance for the efficient operation of logistics enterprises. Through optimization, it is conducive to the sustainable development of enterprises and to achieving long-term profitability.

Suggested Citation

  • Li Zhou & Zhaochan Li & Ning Shi & Shaohua Liu & Ke Xiong, 2019. "Performance Analysis of Three Intelligent Algorithms on Route Selection of Fishbone Layout," Sustainability, MDPI, vol. 11(4), pages 1-17, February.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:4:p:1148-:d:208035
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    References listed on IDEAS

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    Cited by:

    1. Masae, Makusee & Glock, Christoph H. & Vichitkunakorn, Panupong, 2021. "A method for efficiently routing order pickers in the leaf warehouse," International Journal of Production Economics, Elsevier, vol. 234(C).
    2. Rajabighamchi, Farzaneh & van Hoesel, Stan & Defryn, Christof, 2023. "Graph reduction for the planar Travelling Salesman Problem," Research Memorandum 004, Maastricht University, Graduate School of Business and Economics (GSBE).
    3. Li Zhou & Huwei Liu & Junhui Zhao & Fan Wang & Jianglong Yang, 2022. "Performance Analysis of Picking Routing Strategies in the Leaf Layout Warehouse," Mathematics, MDPI, vol. 10(17), pages 1-28, September.

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