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Robust optimization of liner shipping alliance fleet scheduling with consideration of sulfur emission restrictions and slot exchange

Author

Listed:
  • Jihong Chen

    (Shenzhen University
    Commercial College, Xi’an International University)

  • Jun Ye

    (Shenzhen University)

  • Anti Liu

    (Shenzhen University)

  • Yijie Fei

    (Shenzhen University)

  • Zheng Wan

    (University of California Davis)

  • Xiutao Huang

    (Shenzhen University)

Abstract

The International Maritime Organization (IMO) has imposed restrictions on the sulfur content of global marine fuels since 2020, putting the international container shipping and logistics industry under new challenges such as alliance-based operations and emission control for green development and adding to the stress on fleet scheduling of container liner companies. Against this background, this paper studies the fleet scheduling problem of container liner alliance members in the slot exchange mode, with sulfur emission restrictions taken into consideration. It builds an ellipsoidal uncertainty set to describe market demand uncertainties, and includes the changes in fuel surcharges and low-sulfur fuel costs into the robust optimization study of liner fleet scheduling. The minimax regret approach is used to solve the problem and an optimal robust optimization decision-making scheme is obtained, so that liner shipping enterprises can well share risks and allocate profits in uncertainties. The model established in this paper makes predictive analysis of the operations of liner shipping enterprises under the sulfur restriction policy, and provides an effective tool for fleet scheduling decision-making, which offers helpful reference to the survival and development of liner shipping enterprises in the new situation.

Suggested Citation

  • Jihong Chen & Jun Ye & Anti Liu & Yijie Fei & Zheng Wan & Xiutao Huang, 2024. "Robust optimization of liner shipping alliance fleet scheduling with consideration of sulfur emission restrictions and slot exchange," Annals of Operations Research, Springer, vol. 343(3), pages 1013-1043, December.
    • Handle: RePEc:spr:annopr:v:343:y:2024:i:3:d:10.1007_s10479-022-04590-x
    DOI: 10.1007/s10479-022-04590-x
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