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Stochastic scheduling of autonomous mobile robots at hospitals

Author

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  • Lulu Cheng
  • Ning Zhao
  • Mengge Yuan
  • Kan Wu

Abstract

This paper studies the scheduling of autonomous mobile robots (AMRs) at hospitals where the stochastic travel times and service times of AMRs are affected by the surrounding environment. The routes of AMRs are planned to minimize the daily cost of the hospital (including the AMR fixed cost, penalty cost of violating the time window, and transportation cost). To efficiently generate high-quality solutions, some properties are identified and incorporated into an improved tabu search (I-TS) algorithm for problem-solving. Experimental evaluations demonstrate that the I-TS algorithm outperforms existing methods by producing high-quality solutions. Based on the characteristics of healthcare requests and the AMR working environment, scheduling AMRs reasonably can effectively provide medical services, improve the utilization of medical resources, and reduce hospital costs.

Suggested Citation

  • Lulu Cheng & Ning Zhao & Mengge Yuan & Kan Wu, 2023. "Stochastic scheduling of autonomous mobile robots at hospitals," PLOS ONE, Public Library of Science, vol. 18(10), pages 1-24, October.
  • Handle: RePEc:plo:pone00:0292002
    DOI: 10.1371/journal.pone.0292002
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    References listed on IDEAS

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    1. Sebastián Dávila & Miguel Alfaro & Guillermo Fuertes & Manuel Vargas & Mauricio Camargo, 2021. "Vehicle Routing Problem with Deadline and Stochastic Service Times: Case of the Ice Cream Industry in Santiago City of Chile," Mathematics, MDPI, vol. 9(21), pages 1-18, October.
    2. Junlong Zhang & William Lam & Bi Chen, 2013. "A Stochastic Vehicle Routing Problem with Travel Time Uncertainty: Trade-Off Between Cost and Customer Service," Networks and Spatial Economics, Springer, vol. 13(4), pages 471-496, December.
    3. G. Clarke & J. W. Wright, 1964. "Scheduling of Vehicles from a Central Depot to a Number of Delivery Points," Operations Research, INFORMS, vol. 12(4), pages 568-581, August.
    4. Zengliang Han & Dongqing Wang & Feng Liu & Zhiyong Zhao, 2017. "Multi-AGV path planning with double-path constraints by using an improved genetic algorithm," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-16, July.
    5. Davis, L.C., 2017. "Dynamic origin-to-destination routing of wirelessly connected, autonomous vehicles on a congested network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 478(C), pages 93-102.
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