IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i9p5242-d550304.html
   My bibliography  Save this article

Speed Optimization for Container Ship Fleet Deployment Considering Fuel Consumption

Author

Listed:
  • Chao-Feng Gao

    (Logistics Research Center, Shanghai Maritime University, Shanghai 201306, China
    School of Management, Shanghai University of Engineering Science, Shanghai 201620, China)

  • Zhi-Hua Hu

    (Logistics Research Center, Shanghai Maritime University, Shanghai 201306, China)

Abstract

In recent years, low energy consumption has become the common choice of economic development in the world. In order to control energy consumption, shipping line speed optimization has become strategically important. to reduce fuel consumption, this study optimizes the container ship fleet deployment problem by adopting the strategy of adjusting each leg of each route’s sailing speed. To calculate fuel consumption more accurately, both sailing speed and the ship’s payload are considered. A multi-objective mixed integer nonlinear programming model is established to optimize the allocation of liner routes with multiple ship types on multiple routes. A linear outer-approximation algorithm and an improved piecewise linear approximation algorithm are used for linearization. If segments of an interval increase, the results will be more accurate but will take more time to compute. As fuel prices increase, to make trade-offs among economic and environmental considerations, the shipping company is adopting the “adding ship and slow down its speed” strategy, which verifies the validity and applicability of the established model.

Suggested Citation

  • Chao-Feng Gao & Zhi-Hua Hu, 2021. "Speed Optimization for Container Ship Fleet Deployment Considering Fuel Consumption," Sustainability, MDPI, vol. 13(9), pages 1-18, May.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:9:p:5242-:d:550304
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/9/5242/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/9/5242/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Shuaian & Meng, Qiang, 2012. "Liner ship fleet deployment with container transshipment operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(2), pages 470-484.
    2. Chandra, Saurabh & Christiansen, Marielle & Fagerholt, Kjetil, 2016. "Combined fleet deployment and inventory management in roll-on/roll-off shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 92(C), pages 43-55.
    3. Panayotis G Zacharioudakis & Stylianos Iordanis & Dimitrios V Lyridis & Harilaos N Psaraftis, 2011. "Liner shipping cycle cost modelling, fleet deployment optimization and what-if analysis," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 13(3), pages 278-297, September.
    4. Shuaian Wang & Dan Zhuge & Lu Zhen & Chung-Yee Lee, 2021. "Liner Shipping Service Planning Under Sulfur Emission Regulations," Transportation Science, INFORMS, vol. 55(2), pages 491-509, March.
    5. Christiansen, Marielle & Fagerholt, Kjetil & Nygreen, Bjørn & Ronen, David, 2013. "Ship routing and scheduling in the new millennium," European Journal of Operational Research, Elsevier, vol. 228(3), pages 467-483.
    6. Gelareh, Shahin & Pisinger, David, 2011. "Fleet deployment, network design and hub location of liner shipping companies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 947-964.
    7. Wang, Yadong & Meng, Qiang & Du, Yuquan, 2015. "Liner container seasonal shipping revenue management," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 141-161.
    8. D Ronen, 2011. "The effect of oil price on containership speed and fleet size," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 211-216, January.
    9. Harilaos N. Psaraftis, 2019. "Speed Optimization vs Speed Reduction: the Choice between Speed Limits and a Bunker Levy," Sustainability, MDPI, vol. 11(8), pages 1-18, April.
    10. Gelareh, Shahin & Meng, Qiang, 2010. "A novel modeling approach for the fleet deployment problem within a short-term planning horizon," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(1), pages 76-89, January.
    11. Liqian Yang & Gang Chen & Jinlou Zhao & Niels Gorm Malý Rytter, 2020. "Ship Speed Optimization Considering Ocean Currents to Enhance Environmental Sustainability in Maritime Shipping," Sustainability, MDPI, vol. 12(9), pages 1-24, May.
    12. Zhen, Lu & Hu, Yi & Wang, Shuaian & Laporte, Gilbert & Wu, Yiwei, 2019. "Fleet deployment and demand fulfillment for container shipping liners," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 15-32.
    13. Jun Xia & Kevin X. Li & Hong Ma & Zhou Xu, 2015. "Joint Planning of Fleet Deployment, Speed Optimization, and Cargo Allocation for Liner Shipping," Transportation Science, INFORMS, vol. 49(4), pages 922-938, November.
    14. Wang, Xin & Fagerholt, Kjetil & Wallace, Stein W., 2018. "Planning for charters: A stochastic maritime fleet composition and deployment problem," Omega, Elsevier, vol. 79(C), pages 54-66.
    15. Meng, Qiang & Wang, Shuaian, 2012. "Liner ship fleet deployment with week-dependent container shipment demand," European Journal of Operational Research, Elsevier, vol. 222(2), pages 241-252.
    16. Wang, Shuaian & Meng, Qiang, 2012. "Sailing speed optimization for container ships in a liner shipping network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(3), pages 701-714.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xinyu Li & Yi Zuo & Junhao Jiang, 2022. "Application of Regression Analysis Using Broad Learning System for Time-Series Forecast of Ship Fuel Consumption," Sustainability, MDPI, vol. 15(1), pages 1-21, December.
    2. Xiangang Lan & Qin Tao & Xincheng Wu, 2023. "Liner-Shipping Network Design with Emission Control Areas: A Real Case Study," Sustainability, MDPI, vol. 15(4), pages 1-23, February.
    3. Kai Li & Yongqiang Zhuo & Xiaoqing Luo, 2022. "Optimization method of fuel saving and cost reduction of tugboat main engine based on genetic algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 605-614, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lai, Xiaofan & Wu, Lingxiao & Wang, Kai & Wang, Fan, 2022. "Robust ship fleet deployment with shipping revenue management," Transportation Research Part B: Methodological, Elsevier, vol. 161(C), pages 169-196.
    2. Wang, Yadong & Wang, Shuaian, 2021. "Deploying, scheduling, and sequencing heterogeneous vessels in a liner container shipping route," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
    3. Zhen, Lu & Wu, Yiwei & Wang, Shuaian & Laporte, Gilbert, 2020. "Green technology adoption for fleet deployment in a shipping network," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 388-410.
    4. Xi Jiang & Haijun Mao & Yadong Wang & Hao Zhang, 2020. "Liner Shipping Schedule Design for Near-Sea Routes Considering Big Customers’ Preferences on Ship Arrival Time," Sustainability, MDPI, vol. 12(18), pages 1-20, September.
    5. Zhen, Lu & Hu, Yi & Wang, Shuaian & Laporte, Gilbert & Wu, Yiwei, 2019. "Fleet deployment and demand fulfillment for container shipping liners," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 15-32.
    6. Chen, Kang & Chen, Dongxu & Sun, Xueshan & Yang, Zhongzhen, 2016. "Container Ocean-transportation System Design with the factors of demand fluctuation and choice inertia of shippers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 267-281.
    7. Christian Va Karsten & Stefan Ropke & David Pisinger, 2018. "Simultaneous Optimization of Container Ship Sailing Speed and Container Routing with Transit Time Restrictions," Transportation Science, INFORMS, vol. 52(4), pages 769-787, August.
    8. Wang, Xin & Fagerholt, Kjetil & Wallace, Stein W., 2018. "Planning for charters: A stochastic maritime fleet composition and deployment problem," Omega, Elsevier, vol. 79(C), pages 54-66.
    9. Qiang Meng & Shuaian Wang & Henrik Andersson & Kristian Thun, 2014. "Containership Routing and Scheduling in Liner Shipping: Overview and Future Research Directions," Transportation Science, INFORMS, vol. 48(2), pages 265-280, May.
    10. Wang, Shuaian, 2014. "A novel hybrid-link-based container routing model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 165-175.
    11. Manuel Herrera & Per J. Agrell & Casiano Manrique-de-Lara-Peñate & Lourdes Trujillo, 2017. "Vessel capacity restrictions in the fleet deployment problem: an application to the Panama Canal," Annals of Operations Research, Springer, vol. 253(2), pages 845-869, June.
    12. Sun, Qinghe & Li, Wei & Meng, Qiang, 2024. "Single-leg shipping revenue management for expedited services with ambiguous elasticity in transit-time-sensitive demand," Transportation Research Part B: Methodological, Elsevier, vol. 180(C).
    13. Wang, Yadong & Meng, Qiang, 2021. "Optimizing freight rate of spot market containers with uncertainties in shipping demand and available ship capacity," Transportation Research Part B: Methodological, Elsevier, vol. 146(C), pages 314-332.
    14. Zheng, Jianfeng & Qi, Jingwen & Sun, Zhuo & Li, Feng, 2018. "Community structure based global hub location problem in liner shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 1-19.
    15. Akyüz, M. Hakan & Lee, Chung-Yee, 2016. "Service type assignment and container routing with transit time constraints and empty container repositioning for liner shipping service networks," Transportation Research Part B: Methodological, Elsevier, vol. 88(C), pages 46-71.
    16. Zhao, Shuaiqi & Yang, Hualong & Zheng, Jianfeng & Li, Dechang, 2024. "A two-step approach for deploying heterogeneous vessels and designing reliable schedule in liner shipping services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).
    17. Dong, Jing-Xin & Lee, Chung-Yee & Song, Dong-Ping, 2015. "Joint service capacity planning and dynamic container routing in shipping network with uncertain demands," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 404-421.
    18. Christiansen, Marielle & Fagerholt, Kjetil & Nygreen, Bjørn & Ronen, David, 2013. "Ship routing and scheduling in the new millennium," European Journal of Operational Research, Elsevier, vol. 228(3), pages 467-483.
    19. Moussawi-Haidar, Lama & Nasr, Walid & Jalloul, Maya, 2021. "Standardized cargo network revenue management with dual channels under stochastic and time-dependent demand," European Journal of Operational Research, Elsevier, vol. 295(1), pages 275-291.
    20. Wang, Shuaian & Meng, Qiang, 2012. "Liner ship route schedule design with sea contingency time and port time uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 46(5), pages 615-633.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:9:p:5242-:d:550304. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.