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Solving the cooperative scheduling problem of muck transport under time-segment restriction in an entire region

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Abstract

With the acceleration of urbanization, there is an urgent need to build more transportation facilities to alleviate travel pressure. However, during the construction of a subway station, a large amount of muck is generated and must be transported to a treatment center. In response to transportation policies, this paper establishes a regional and time-limited transportation model for muck trucks based on their departure time points. The model aims to dispatch the least number of vehicles and complete all transportation tasks as quickly as possible, taking into account constraints such as restricted travel time. This paper uses the NSGA-II algorithm with multi-segment encoding to solve this problem, and numerical experiments are conducted to analyze the performance of the proposed method. The results indicate that the improved algorithm has better convergence and distribution than the standard NSGA-II. The study also validates the effectiveness of the proposed method through a real-world example of muck transportation at subway stations in a specific city. The collaborative scheduling schemes developed through the methods proposed in this paper have effectively avoided the travel restriction period, providing managers with multiple decision-making options.

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Acknowledgements

The authors are very thankful to an anonymous reviewer who provided feedback that helped to improve the quality, accuracy and presentation of this study.

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Authors and Affiliations

  1. College of Energy and Mining Engineering, Shandong University of Science and Technology, Qingdao, 266590, China

    Duanyi Wang, Zhaoxia Liu, Lin Chen, Mengxiao Wei, Zongrong Li & Yuming Li

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  1. Duanyi Wang
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  2. Zhaoxia Liu
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  3. Lin Chen
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Correspondence to Zhaoxia Liu.

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Wang, D., Liu, Z., Chen, L. et al. Solving the cooperative scheduling problem of muck transport under time-segment restriction in an entire region. Appl Intell 54, 317–333 (2024). https://doi.org/10.1007/s10489-023-05189-w

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