IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i22p6367-d286350.html
   My bibliography  Save this article

Tramp Ship Routing and Scheduling with Speed Optimization Considering Carbon Emissions

Author

Listed:
  • Houming Fan

    (College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China)

  • Jiaqi Yu

    (College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China)

  • Xinzhe Liu

    (College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China)

Abstract

The International Maritime Organization (IMO) proposed to reduce the total CO 2 emissions of the maritime sector by 50% by 2050, and strive to gradually achieve the zero-carbon target. Therefore, shipping companies need to consider environmental impacts while pursuing benefits. In view of the tramp ship scheduling with speed optimization problem, considering carbon emissions, the configuration of owner ships and charter ships, and the impact of sailing speed on ship scheduling with the target of minimizing the total costs of shipping companies, multi-type tramp ship scheduling and speed optimization considering carbon emissions is established. A genetic simulated annealing algorithm based on a variable neighborhood search is proposed to solve the problem. Firstly, the ship type is matched with the cargo. Then the route is generated according to the time constraint, and finally, the neighborhood search strategy is adopted to improve the solution quality. The effectiveness of the proposed model and algorithm is verified by an example, which also confirms that ship scheduling and sailing speed joint optimization can reduce costs and carbon emissions. Research results can not only deepen the study of the theory of tramp scheduling but also to effectively solve the tramp shipping schedule considering carbon emissions problems faced by companies to provide theoretical guidance.

Suggested Citation

  • Houming Fan & Jiaqi Yu & Xinzhe Liu, 2019. "Tramp Ship Routing and Scheduling with Speed Optimization Considering Carbon Emissions," Sustainability, MDPI, vol. 11(22), pages 1-19, November.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:22:p:6367-:d:286350
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/22/6367/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/22/6367/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wu, Lingxiao & Pan, Kai & Wang, Shuaian & Yang, Dong, 2018. "Bulk ship scheduling in industrial shipping with stochastic backhaul canvassing demand," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 117-136.
    2. Hennig, F. & Nygreen, B. & Furman, K.C. & Song, J., 2015. "Alternative approaches to the crude oil tanker routing and scheduling problem with split pickup and split delivery," European Journal of Operational Research, Elsevier, vol. 243(1), pages 41-51.
    3. Meng, Qiang & Wang, Shuaian & Lee, Chung-Yee, 2015. "A tailored branch-and-price approach for a joint tramp ship routing and bunkering problem," Transportation Research Part B: Methodological, Elsevier, vol. 72(C), pages 1-19.
    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. 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.
    2. 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.
    3. Alba Martínez-López & Manuel Chica, 2020. "Joint Optimization of Routes and Container Fleets to Design Sustainable Intermodal Chains in Chile," Sustainability, MDPI, vol. 12(6), pages 1-23, March.
    4. Fei Teng & Qing Zhang & Tao Zou & Jun Zhu & Yonggang Tu & Qian Feng, 2022. "Energy Management Strategy for Seaport Integrated Energy System under Polymorphic Network," Sustainability, MDPI, vol. 15(1), pages 1-22, December.

    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. Rigot-Müller, Patrick & Cheaitou, Ali & Etienne, Laurent & Faury, Olivier & Fedi, Laurent, 2022. "The role of polarseaworthiness in shipping planning for infrastructure projects in the Arctic: The case of Yamal LNG plant," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 330-353.
    2. Pache, Hannah & Grafelmann, Michaela & Schwientek, Anne Kathrina & Jahn, Carlos, 2020. "Tactical planning in tramp shipping - A literature review," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability. Proceedings of the Hamburg International Conferen, volume 30, pages 281-308, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    3. Magirou, Evangelos F. & Psaraftis, Harilaos N. & Bouritas, Theodore, 2015. "The economic speed of an oceangoing vessel in a dynamic setting," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 48-67.
    4. Wu, Lingxiao & Pan, Kai & Wang, Shuaian & Yang, Dong, 2018. "Bulk ship scheduling in industrial shipping with stochastic backhaul canvassing demand," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 117-136.
    5. Wang, Shuaian & Qu, Xiaobo & Yang, Ying, 2015. "Estimation of the perceived value of transit time for containerized cargoes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 298-308.
    6. Eisuke Watanabe & Ryuichi Shibasaki, 2023. "Extraction of Bunkering Services from Automatic Identification System Data and Their International Comparisons," Sustainability, MDPI, vol. 15(24), pages 1-19, December.
    7. Wu, Weitiao & Liu, Ronghui & Jin, Wenzhou, 2016. "Designing robust schedule coordination scheme for transit networks with safety control margins," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 495-519.
    8. Santos, A.M.P. & Fagerholt, Kjetil & Laporte, Gilbert & Guedes Soares, C., 2022. "A stochastic optimization approach for the supply vessel planning problem under uncertain demand," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 209-228.
    9. Zhen, Lu & Wang, Shuaian & Zhuge, Dan, 2017. "Dynamic programming for optimal ship refueling decision," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 100(C), pages 63-74.
    10. Pache, Hannah & Kastner, Marvin & Jahn, Carlos, 2019. "Current state and trends in tramp ship routing and scheduling," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Digital Transformation in Maritime and City Logistics: Smart Solutions for Logistics. Proceedings of the Hamburg International Conference of Logistics, volume 28, pages 369-394, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    11. De, Arijit & Choudhary, Alok & Turkay, Metin & Tiwari, Manoj K., 2021. "Bunkering policies for a fuel bunker management problem for liner shipping networks," European Journal of Operational Research, Elsevier, vol. 289(3), pages 927-939.
    12. Wang, Shuang & Wallace, Stein W. & Lu, Jing & Gu, Yewen, 2020. "Handling financial risks in crude oil imports: Taking into account crude oil prices as well as country and transportation risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    13. Bor-Hong Lin & Hsuan-Shih Lee & Cheng-Chi Chung, 2020. "The Construction and Implication of Group Scale Efficiency Evaluation Model for Bulk Shipping Corporations," Mathematics, MDPI, vol. 8(5), pages 1-13, May.
    14. Wu, Lingxiao & Wang, Shuaian & Laporte, Gilbert, 2021. "The Robust Bulk Ship Routing Problem with Batched Cargo Selection," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 124-159.
    15. Zhang, Guowei & Jia, Ning & Zhu, Ning & Adulyasak, Yossiri & Ma, Shoufeng, 2023. "Robust drone selective routing in humanitarian transportation network assessment," European Journal of Operational Research, Elsevier, vol. 305(1), pages 400-428.
    16. Wang, Shuang & Jia, Haiying & Lu, Jing & Yang, Dong, 2023. "Crude oil transportation route choices: A connectivity reliability-based approach," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    17. Gao, Zhendi & Ji, Mingjun & Kong, Lingrui & Hou, Xinhao, 2024. "Scheduling of automated ore terminal operations based on fixed inflow rhythm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).
    18. Kazemi, Ahmad & Ernst, Andreas T. & Krishnamoorthy, Mohan & Le Bodic, Pierre, 2021. "Locomotive fuel management with inline refueling," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1077-1096.
    19. Christiansen, Marielle & Fagerholt, Kjetil & Rachaniotis, Nikolaos P. & Stålhane, Magnus, 2017. "Operational planning of routes and schedules for a fleet of fuel supply vessels," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 163-175.
    20. Liu, Baoli & Li, Zhi-Chun & Wang, Yadong & Sheng, Dian, 2021. "Short-term berth planning and ship scheduling for a busy seaport with channel restrictions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).

    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:11:y:2019:i:22:p:6367-:d:286350. 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.