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Liner shipping cycle cost modelling, fleet deployment optimization and what-if analysis

Author

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  • Panayotis G Zacharioudakis

    (Laboratory for Maritime Transport 9, National Technical University of Athens, School of Naval Architecture and Marine Engineering, Heroon Polytechniou St, Zografou, Athens 15773, Greece.)

  • Stylianos Iordanis

    (Laboratory for Maritime Transport 9, National Technical University of Athens, School of Naval Architecture and Marine Engineering, Heroon Polytechniou St, Zografou, Athens 15773, Greece.)

  • Dimitrios V Lyridis

    (Laboratory for Maritime Transport 9, National Technical University of Athens, School of Naval Architecture and Marine Engineering, Heroon Polytechniou St, Zografou, Athens 15773, Greece.)

  • Harilaos N Psaraftis

    (Laboratory for Maritime Transport 9, National Technical University of Athens, School of Naval Architecture and Marine Engineering, Heroon Polytechniou St, Zografou, Athens 15773, Greece.)

Abstract

This article formulates the mathematical model of the liner shipping company cycle cost and attempts to optimize the operational profile of company assets in regards to specific network of routes of cargo flows and vessels portfolio. In other words it attempts to give a practical solution to the modern shipping company fleet deployment problem. This is achieved by developing a generic cost model methodology that aims to minimize total operating costs by using Genetic Algorithms in optimizing various predefined attributes such as operational speed. The finalized model could be applicable to liner shipping companies for optimization purposes of liner networks, as well as for simulation and examination of possible scenarios and what-if analysis. In the era of recession, a demand shock is examined and, interesting results are produced. In further research, this model can estimate the impact of environmental legislation intensification. In the what-if analysis, the model can depict how an initial design of a liner system can be optimized by modifying system attributes to dynamically meet new requirements.

Suggested Citation

  • 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.
    • Handle: RePEc:pal:marecl:v:13:y:2011:i:3:p:278-297
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    Citations

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    Cited by:

    1. 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.
    2. Nguyen Khoi Tran & Hans-Dietrich Haasis & Tobias Buer, 2017. "Container shipping route design incorporating the costs of shipping, inland/feeder transport, inventory and CO2 emission," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(4), pages 667-694, December.
    3. 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.
    4. Furkan Oztanriseven & Heather Nachtmann, 2020. "Modeling dynamic behavior of navigable inland waterways," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 22(2), pages 173-195, June.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Kian-Guan Lim & Michelle Lim, 2020. "Financial performance of shipping firms that increase LNG carriers and the support of eco-innovation," Journal of Shipping and Trade, Springer, vol. 5(1), pages 1-25, December.

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