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Comparative analysis of different routing heuristics for the battery management of automated guided vehicles

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  • Qazi Shaheen Kabir
  • Yoshinori Suzuki

Abstract

This paper explores how different routing techniques for the battery management of automated guided vehicles (AGVs) can affect the performance of a system. Four heuristics available in the literature were the basis of this study. Simulation models were developed to investigate how the routing of an AGV towards a battery station can affect the productivity of a manufacturing facility. Results show that the best productivity can be achieved when a routing heuristic tries to jointly minimise the total travel distance and waiting time at a battery station. The gain in productivity, when compared with the highest possible gain theoretically achievable, is quite substantial. It was also found that higher frequency of decision-making (i.e. decisions with smaller time interval) about battery swapping helps to increase the productivity of a system.

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  • Qazi Shaheen Kabir & Yoshinori Suzuki, 2019. "Comparative analysis of different routing heuristics for the battery management of automated guided vehicles," International Journal of Production Research, Taylor & Francis Journals, vol. 57(2), pages 624-641, January.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:2:p:624-641
    DOI: 10.1080/00207543.2018.1475761
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    Cited by:

    1. Li, Xiangda & Peng, Yun & Tian, Qi & Feng, Tao & Wang, Wenyuan & Cao, Zhen & Song, Xiangqun, 2023. "A decomposition-based optimization method for integrated vehicle charging and operation scheduling in automated container terminals under fast charging technology," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
    2. Chen, Wanying & Gong, Yeming & Chen, Qi & Wang, Hongwei, 2024. "Does battery management matter? Performance evaluation and operating policies in a self-climbing robotic warehouse," European Journal of Operational Research, Elsevier, vol. 312(1), pages 164-181.
    3. Fragapane, Giuseppe & de Koster, René & Sgarbossa, Fabio & Strandhagen, Jan Ola, 2021. "Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda," European Journal of Operational Research, Elsevier, vol. 294(2), pages 405-426.
    4. Lv, Jie & Lin, Shili & Song, Wenji & Chen, Mingbiao & Feng, Ziping & Li, Yongliang & Ding, Yulong, 2019. "Performance of LiFePO4 batteries in parallel based on connection topology," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    5. Seokgi Lee & Hyun Woo Jeon & Mona Issabakhsh & Ahmad Ebrahimi, 2022. "An electric forklift routing problem with battery charging and energy penalty constraints," Journal of Intelligent Manufacturing, Springer, vol. 33(6), pages 1761-1777, August.
    6. Lu, Ying & Fang, Sidun & Niu, Tao & Liao, Ruijin, 2023. "Energy-transport scheduling for green vehicles in seaport areas: A review on operation models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).

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