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A Building-Block-Based Genetic Algorithm for Solving the Robots Allocation Problem in a Robotic Mobile Fulfilment System

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  • Jingtian Zhang
  • Fuxing Yang
  • Xun Weng

Abstract

Robotic mobile fulfilment system (RMFS) is an efficient and flexible order picking system where robots ship the movable shelves with items to the picking stations. This innovative parts-to-picker system, known as Kiva system, is especially suited for e-commerce fulfilment centres and has been widely used in practice. However, there are lots of resource allocation problems in RMFS. The robots allocation problem of deciding which robot will be allocated to a delivery task has a significant impact on the productivity of the whole system. We model this problem as a resource-constrained project scheduling problem with transfer times (RCPSPTT) based on the accurate analysis of driving and delivering behaviour of robots. A dedicated serial schedule generation scheme and a genetic algorithm using building-blocks-based crossover (BBX) operator are proposed to solve this problem. The designed algorithm can be combined into a dynamic scheduling structure or used as the basis of calculation for other allocation problems. Experiment instances are generated based on the characteristics of RMFS, and the computation results show that the proposed algorithm outperforms the traditional rule-based scheduling method. The BBX operator is rapid and efficient which performs better than several classic and competitive crossover operators.

Suggested Citation

  • Jingtian Zhang & Fuxing Yang & Xun Weng, 2019. "A Building-Block-Based Genetic Algorithm for Solving the Robots Allocation Problem in a Robotic Mobile Fulfilment System," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-15, February.
    • Handle: RePEc:hin:jnlmpe:6153848
    DOI: 10.1155/2019/6153848
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    Cited by:

    1. Jianming Cai & Xiaokang Li & Yue Liang & Shan Ouyang, 2021. "Collaborative Optimization of Storage Location Assignment and Path Planning in Robotic Mobile Fulfillment Systems," Sustainability, MDPI, vol. 13(10), pages 1-26, May.
    2. Justkowiak, Jan-Erik & Pesch, Erwin, 2023. "Stronger mixed-integer programming-formulations for order- and rack-sequencing in robotic mobile fulfillment systems," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1063-1078.
    3. Liu, Ying & Zhou, Jing & Lim, Andrew & Hu, Qian, 2023. "A tree search heuristic for the resource constrained project scheduling problem with transfer times," European Journal of Operational Research, Elsevier, vol. 304(3), pages 939-951.
    4. Xie, Lin & Thieme, Nils & Krenzler, Ruslan & Li, Hanyi, 2021. "Introducing split orders and optimizing operational policies in robotic mobile fulfillment systems," European Journal of Operational Research, Elsevier, vol. 288(1), pages 80-97.
    5. Justkowiak, Jan-Erik & Pesch, Erwin, 2023. "A column generation driven heuristic for order-scheduling and rack-sequencing in robotic mobile fulfillment systems," Omega, Elsevier, vol. 120(C).

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