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Green Liner Shipping Network Design

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Abstract

Green Liner Shipping Network Design refers to the problems in green logistics related to the design of maritime services in liner shipping with a focus on reducing the environmental impact. This chapter discusses how to more efficiently plan the vessel services with the use of mathematical optimization models. A brief introduction to the main characteristics of Liner Shipping Network Design is given, as well as the different variants and assumptions that can be considered when defining this problem. The chapter also includes an overview of the algorithms and approaches that have been presented in the literature to design such networks.

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References

  • Agarwal, R., & Ergun, Ö. (2008). Ship scheduling and network design for cargo routing in liner shipping. Transportation Science, 42(2), 175–196.

    Article  Google Scholar 

  • Ahuja, R. K., Magnanti, T. L., & Orlin, J. B. (1993). Network flows: Theory, algorithms, and applications. Englewood Cliffs: Prentice Hall.

    Google Scholar 

  • Álvarez, J. F. (2009). Joint routing and deployment of a fleet of container vessels. Maritime Economics & Logistics, 11(2), 186–208.

    Article  Google Scholar 

  • Archetti, C., & Speranza, M. G. (2014). A survey on matheuristics for routing problems. EURO Journal on Computational Optimization, 2(4), 223–246.

    Article  Google Scholar 

  • Balakrishnan, A., & Karsten, C. V. (2017). Container shipping service selection and cargo routing with transshipment limits. European Journal of Operational Research, 263(2), 652–663.

    Article  Google Scholar 

  • Brouer, B. D., Álvarez, J. F., Plum, C. E. M., Pisinger, D., & Sigurd, M. M. (2014a). A base integer programming model and benchmark suite for liner-shipping network design. Transportation Science, 48(2), 281–312.

    Article  Google Scholar 

  • Brouer, B. D., Desaulniers, G., & Pisinger, D. (2014b). A matheuristic for the liner shipping network design problem. Transportation Research Part E: Logistics and Transportation Review, 72, 42–59.

    Article  Google Scholar 

  • Brouer, B. D., Desaulniers, G., Karsten, C. V., & Pisinger, D. (2015). A matheuristic for the liner shipping network design problem with transit time restrictions. In F. Corman, S. Voß, & R. R. Negenborn (Eds.), Computational logistics (pp. 195–208). Cham: Springer.

    Chapter  Google Scholar 

  • Brouer, B. D., Karsten, C. V., & Pisinger, D. (2016). Big data optimization in maritime logistics. In A. Emrouznejad (Ed.), Big data optimization: Recent developments and challenges (Studies in big data, Vol. 18, pp. 319–344). Cham: Springer.

    Google Scholar 

  • Brouer, B. D., Karsten, C. V., & Pisinger, D. (2017). Optimization in liner shipping. 4OR, 15(1), 1–35.

    Article  Google Scholar 

  • Christiansen, M., Fagerholt, K., & Ronen, D. (2004). Ship routing and scheduling: Status and perspectives. Transportation Science, 38(1), 1–18.

    Article  Google Scholar 

  • Christiansen, M., Fagerholt, K., Nygreen, B., & Ronen, D. (2013). Ship routing and scheduling in the new millennium. European Journal of Operational Research, 228(3), 467–483.

    Article  Google Scholar 

  • Dithmer, P., Reinhardt, L. B., & Kontovas, C. A. (2017). The liner shipping routing and scheduling problem under environmental considerations: The case of emissions control areas. In International Conference on Computational Logistics (pp. 336–350). Springer.

    Google Scholar 

  • Fagerholt, K., Gausel, N. T., Rakke, J. G., & Psaraftis, H. N. (2015). Maritime routing and speed optimization with emission control areas. Transportation Research Part C: Emerging Technologies, 52, 57–73.

    Article  Google Scholar 

  • Germanischer Lloyd. (2013). http://www.balkanlloyd.com/news/96-germanischer-lloyd-has-conducted-research-showing-that-new-and-efficient-4-500-teu-panamax. [Online; Accessed 20 Feb 2017].

  • Hansen, P., & Mladenovic, N. (2014). Variable neighborhood search. In E. K. Burke & G. Kendall (Eds.), Search methodologies – Introductory tutorials in optimization and decision support techniques (pp. 313–337). New York: Springer.

    Google Scholar 

  • IMO. (2014). Third imo greenhouse gas study 2014. Technical report, International Maritime Organization.

    Google Scholar 

  • Karsten, C. V. (2015). Competitive liner shipping network design.Ph. D. Thesis, DTU Management Engineering.

    Google Scholar 

  • Karsten, C. V., Pisinger, D., Røpke, S., & Brouer, B. D. (2015). The time constrained multi-commodity network flow problem and its application to liner shipping network design. Transportation Research Part E: Logistics and Transportation Review, 76, 122–138.

    Article  Google Scholar 

  • Karsten, C. V., Brouer, B. D., & Pisinger, D. (2017a). Competitive liner shipping network design. Computers & Operations Research, 87, 125–136.

    Article  Google Scholar 

  • Karsten, C. V., Brouer, B. D., Desaulniers, G., & Pisinger, D. (2017b). Time constrained liner shipping network design. Transportation Research. Part E: Logistics and Transportation Review, 105, 152–162.

    Article  Google Scholar 

  • Karsten, C. V., Røpke, S., & Pisinger, D. (2018). Simultaneous optimization of container ship sailing speed and container routing with transit time restrictions. Transportation Science, 52(4), 739–1034.

    Article  Google Scholar 

  • Kim, H. J. (2013). A lagrangian heuristic for determining the speed and bunkering port of a ship. Journal of the Operational Research Society, 65(5), 747–754.

    Article  Google Scholar 

  • Kontovas, C. A. (2014). The green ship routing and scheduling problem (GSRSP): A conceptual approach. Transportation Research Part D: Transport and Environment, 31, 61–69.

    Article  Google Scholar 

  • Krogsgaard, A., Pisinger, D., & Thorsen, J. (2018). A flow-first route-next heuristic for liner shipping network design. Transportation Science, 72(3), 358–381. Special Issue on Emerging Challenges in Transportation Planning.

    Article  Google Scholar 

  • Lee, C.-Y., & Song, D.-P. (2017). Ocean container transport in global supply chains: Overview and research opportunities. Transportation Research Part B: Methodological, 95, 442–474.

    Article  Google Scholar 

  • Li, C., Qi, X., & Lee, C.-Y. (2015). Disruption recovery for a vessel in liner shipping. Transportation Science, 49(4), 900–921.

    Article  Google Scholar 

  • Maersk. (2017). The world’s largest ship. https://www.maersk.com/en/explore/fleet/triple-e/environment

  • Meng, Q., & Wang, S. (2011a). Optimal operating strategy for a long-haul liner service route. European Journal of Operational Research, 215(1), 105–114.

    Article  Google Scholar 

  • Meng, Q., & Wang, S. (2011b). Liner shipping service network design with empty container repositioning. Transportation Research Part E: Logistics and Transportation Review, 47(5), 695–708.

    Article  Google Scholar 

  • Meng, Q., Wang, S., Andersson, H., & Thun, K. (2014). Containership routing and scheduling in liner shipping: Overview and future research directions. Transportation Science, 48, 265–280.

    Article  Google Scholar 

  • Miller, C. E., Tucker, A. W., & Zemlin, R. A. (1960). Integer programming formulation of traveling salesman problems. Journal of the ACM (JACM), 7(4), 326–329.

    Article  Google Scholar 

  • Montreuil, B. (2011). Towards a physical internet: Meeting the global logisitcs sustainability grand challenge. Logistics Research, 3, 71–87.

    Article  Google Scholar 

  • Neamatian Monemi, R., & Gelareh, S. (2017). Network design, fleet deployment and empty repositioning in liner shipping. Transportation Research Part E, 108, 60–79.

    Article  Google Scholar 

  • Notteboom, T. E. (2006). The time factor in liner shipping services. Maritime Economics & Logistics, 8(1), 19–39.

    Article  Google Scholar 

  • Notteboom, T. E., & Vernimmen, B. (2009). The effect of high fuel costs on liner service configuration in container shipping. Journal of Transport Geography, 17,(5), 325–337.

    Article  Google Scholar 

  • Plum, C. E. M., Pisinger, D., & Sigurd, M. M. (2014). A service flow model for the liner shipping network design problem. European Journal of Operational Research, 235(2), 378–386.

    Article  Google Scholar 

  • Psaraftis, H. N., & Kontovas, C. A. (2013). Speed models for energy-efficient maritime transportation: A taxonomy and survey. Transportation Research Part C: Emerging Technologies, 26, 331–351.

    Article  Google Scholar 

  • Psaraftis, H. N., & Kontovas, C. A. (2015). Slow steaming in maritime transportation: Fundamentals, trade-offs, and decision models. In C.-Y. Lee & Q. Meng (Eds.), Handbook of ocean container transport logistics: Making global supply chains effective (pp. 315–358). Heidelberg: Springer.

    Google Scholar 

  • Reinhardt, L. B., & Pisinger, D. (2012). A branch and cut algorithm for the container shipping network design problem. Flexible Services and Manufacturing Journal, 24(3), 349–374.

    Article  Google Scholar 

  • Reinhardt, L. B., Plum, C. E. M., Pisinger, D., Sigurd, M. M., & Vial, G. T. P. (2016). The liner shipping berth scheduling problem with transit times. Transportation Research Part E: Logistics and Transportation Review, 86, 116–128.

    Article  Google Scholar 

  • Ronen, D. (1983). Cargo ships routing and scheduling: Survey of models and problems. European Journal of Operational Research, 12(2), 119–126.

    Article  Google Scholar 

  • Ronen, D. (1993). Ship scheduling: The last decade. European Journal of Operational Research, 71(3), 325–333.

    Article  Google Scholar 

  • Ronen, D. (2011). The effect of oil price on containership speed and fleet size. Journal of the Operational Research Society, 62(1), 211–216.

    Article  Google Scholar 

  • Stopford, M. (2009). Maritime economics (3rd ed.). London: Taylor & Francis Ltd. ISBN:9780415275583.

    Google Scholar 

  • Sun, Z., & Zheng, J. (2016). Finding potential hub locations for liner shipping. Transportation Research Part B: Methodological, 93, 750–761.

    Article  Google Scholar 

  • Thun, K., Andersson, H., & Christiansen, M. (2017). Analyzing complex service structures in liner shipping network design. Flexible Services and Manufacturing Journal, 29(3–4), 535–552.

    Article  Google Scholar 

  • Toth, P., & Vigo, D. (2015). Vehicle routing: Problems, methods and applications (Vol. 18). Philadelphia: SIAM.

    Google Scholar 

  • Unctad. (2017a). Review of maritime transport. Technical report, United Nations Conference on Trade and Development.

    Google Scholar 

  • Unctad. (2017b). UnctadSTAT. http://unctadstat.unctad.org/wds/TableViewer/tableView.aspx. [Online; Accessed 9 Feb 2017].

  • Wan, Z., Zhu, M., Chen, S., & Sperling, D. (2016). Pollution: Three steps to a green shipping industry. Nature, 530, 275.

    Article  Google Scholar 

  • Wang, S., & Meng, Q. (2012). Sailing speed optimization for container ships in a liner shipping network. Transportation Research Part E: Logistics and Transportation Review, 48(3), 701–714.

    Article  Google Scholar 

  • Wang, S., & Meng, Q. (2014). Liner shipping network design with deadlines. Computers & Operations Research, 41, 140–149.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. DTU Management Engineering, Technical University of Denmark, Kongens Lyngby, Denmark

    Erik Hellsten, David Pisinger, David Sacramento & Charlotte Vilhelmsen

Authors
  1. Erik Hellsten
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  2. David Pisinger
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  3. David Sacramento
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  4. Charlotte Vilhelmsen
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Corresponding author

Correspondence to David Pisinger .

Editor information

Editors and Affiliations

  1. DTU Management Engineering, Technical University of Denmark, Kongens Lyngby, Denmark

    Harilaos N. Psaraftis

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Hellsten, E., Pisinger, D., Sacramento, D., Vilhelmsen, C. (2019). Green Liner Shipping Network Design. In: Psaraftis, H. (eds) Sustainable Shipping. Springer, Cham. https://doi.org/10.1007/978-3-030-04330-8_9

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