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An analysis on convergence of data-driven approach to ship lock scheduling

Author

Listed:
  • Wang, Xiaoping
  • Zhao, Yunliang
  • Sun, Peng
  • Wang, Xiaobin

Abstract

In this paper, a ship lock scheduling problem is investigated. Ships arrive randomly over time, and the instantaneous arrival rates are allowed to vary both temporally and stochastically in an arbitrary manner. A data-driven approach is applied to a single ship lock scheduling, which is a typical optimizing and decision-making problem. The objective is to minimize the operation costs and other costs(e.g. water cost, electricity cost, and staff welfare cost) by selecting an appropriate slot number during a planned period. The convergence of data-driven approach is discussed from three aspects: the convergence of ant colony optimization algorithm, the convergence of the proposed algorithm, and the error between the historical ship data and the current arrival ship data. The research findings are beneficial for the convergence analysis of data-driven theory and the management of waterway transportation.

Suggested Citation

  • Wang, Xiaoping & Zhao, Yunliang & Sun, Peng & Wang, Xiaobin, 2013. "An analysis on convergence of data-driven approach to ship lock scheduling," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 88(C), pages 31-38.
    • Handle: RePEc:eee:matcom:v:88:y:2013:i:c:p:31-38
    DOI: 10.1016/j.matcom.2013.03.005
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    References listed on IDEAS

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    Cited by:

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    2. Yuan, Yanbin & Ji, Bin & Yuan, Xiaohui & Huang, Yuehua, 2015. "Lockage scheduling of Three Gorges-Gezhouba dams by hybrid of chaotic particle swarm optimization and heuristic-adjusted strategies," Applied Mathematics and Computation, Elsevier, vol. 270(C), pages 74-89.

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