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An utility-based decision support sustainability model in slow steaming maritime operations

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  • Wong, Eugene Y.C.
  • Tai, Allen H.
  • Lau, Henry Y.K.
  • Raman, Mardjuki

Abstract

This paper analyses slow steaming sustainability initiatives and generalizes the traditional discrete cost-based decision support model into novel continuous utility-based models. Two models based on logarithmic and linear utility functions are developed for risk-averse and risk-neutral decision makers respectively. The models, considering fuel consumption, carbon emission, and on time delivery, are applied to a Trans-pacific trade service route. A sensitivity analysis is conducted on parameters of sailing distance, expected transit time, quantity, and emission policies. The model contributes to ship liners on the optimal speed decisions in continuous utility-based slow steaming operations.

Suggested Citation

  • Wong, Eugene Y.C. & Tai, Allen H. & Lau, Henry Y.K. & Raman, Mardjuki, 2015. "An utility-based decision support sustainability model in slow steaming maritime operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 78(C), pages 57-69.
  • Handle: RePEc:eee:transe:v:78:y:2015:i:c:p:57-69
    DOI: 10.1016/j.tre.2015.01.013
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    Cited by:

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    2. Ali Cheaitou & Pierre Cariou, 2019. "Greening of maritime transportation: a multi-objective optimization approach," Annals of Operations Research, Springer, vol. 273(1), pages 501-525, February.
    3. Lee, Chung-Yee & Song, Dong-Ping, 2017. "Ocean container transport in global supply chains: Overview and research opportunities," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 442-474.
    4. Yuzhe Zhao & Yujun Fan & Jingmiao Zhou & Haibo Kuang, 2019. "Bi-Objective Optimization of Vessel Speed and Route for Sustainable Coastal Shipping under the Regulations of Emission Control Areas," Sustainability, MDPI, vol. 11(22), pages 1-24, November.
    5. Yan, Ran & Wang, Shuaian & Psaraftis, Harilaos N., 2021. "Data analytics for fuel consumption management in maritime transportation: Status and perspectives," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
    6. Wang, Shuaian & Wang, Xinchang, 2016. "A polynomial-time algorithm for sailing speed optimization with containership resource sharing," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 394-405.
    7. Assunta Di Vaio & Luisa Varriale, 2018. "Management Innovation for Environmental Sustainability in Seaports: Managerial Accounting Instruments and Training for Competitive Green Ports beyond the Regulations," Sustainability, MDPI, vol. 10(3), pages 1-35, March.
    8. Junayed Pasha & Maxim A. Dulebenets & Masoud Kavoosi & Olumide F. Abioye & Oluwatosin Theophilus & Hui Wang & Raphael Kampmann & Weihong Guo, 2020. "Holistic tactical-level planning in liner shipping: an exact optimization approach," Journal of Shipping and Trade, Springer, vol. 5(1), pages 1-35, December.
    9. Riccardo Giusti & Daniele Manerba & Roberto Tadei, 2021. "Smart Steaming: A New Flexible Paradigm for Synchromodal Logistics," Sustainability, MDPI, vol. 13(9), pages 1-21, April.
    10. Yewen Gu & Stein W. Wallace & Xin Wang, 2017. "The Impact of Bunker Risk Management on CO2 Emissions in Maritime Transportation Under ECA Regulation," Springer Optimization and Its Applications, in: Didem Cinar & Konstantinos Gakis & Panos M. Pardalos (ed.), Sustainable Logistics and Transportation, pages 199-224, Springer.
    11. Dimitrios Georgoulas & Ioannis Koliousis & Stratos Papadimitriou, 2023. "An AHP enabled port selection multi-source decision support system and validation: insights from the ENIRISST project," Journal of Shipping and Trade, Springer, vol. 8(1), pages 1-11, December.
    12. Mallidis, Ioannis & Iakovou, Eleftherios & Dekker, Rommert & Vlachos, Dimitrios, 2018. "The impact of slow steaming on the carriers’ and shippers’ costs: The case of a global logistics network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 18-39.

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