4.5 Article

Carbon-efficient scheduling problem of electric rubber-tyred gantry cranes in a container terminal

Journal

ENGINEERING OPTIMIZATION
Volume 54, Issue 12, Pages 2034-2052

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/0305215X.2021.1972293

Keywords

Carbon-efficient; yard crane scheduling; SVRPSTW; column generation; branch-and-bound

Funding

  1. Key R&D project of Liaoning Provincial Department of Science and Technology [2020JH2/10100042]
  2. National Natural Science Foundation of China [71671021]

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This study explores the ERTG scheduling problem in container terminal yards, converting it into a SVRPSTW and formulating it as a mixed integer linear programming model. A column generation algorithm is employed to solve the problem, with a hybrid acceleration strategy combining label-setting and tabu search algorithms. The proposed method provides an efficient tool for carbon-efficient scheduling of ERTGs, contributing to the development of green ports.
Green container terminals have gained much attention to satisfy the demand for sustainable and environmentally friendly transport. As one of the major polluters in container terminals, rubber-tyred gantry cranes have already been widely replaced by electric rubber-tyred gantry cranes (ERTGs). This article exploits the features of ERTGs and studies the ERTG scheduling problem in container terminal yards considering the carbon dioxide emissions and task delays simultaneously. The problem is converted into a selective vehicle routing problem with soft time windows (SVRPSTW) and formulated as a mixed integer linear programming model. A column generation algorithm embedded in a branch-and-bound framework is employed to solve the problem. A hybrid acceleration strategy combining the label-setting algorithm with a tabu search algorithm is proposed. Finally, the proposed method is validated via computational experiments. The proposed method provides an efficient tool for carbon-efficient scheduling of ERTGs and thus contributes to the development of green ports.

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