Abstract
Liner carriers change their network on a regular basis, and they are therefore interested in a practical evaluation of the impact these changes have on the cargo flows in their networks. Despite great advancements in the practical applicability of network evaluators in recent years, vessel deployment continues to be considered as an input into the problem, rather than a decision. In this paper, we propose an extension of a state-of-the-art mixed integer programming model for the LSCAP that incorporates the optimization of vessel count and vessel classes for each service. We perform a computational analysis on liner shipping networks of different sizes and compare our optimized results to fixed deployment scenarios. By integrating fleet deployment decisions into the cargo allocation problem, liner carriers can increase the profitability of their networks by at least 2.8 to 16.9% and greatly enhance their decision making.
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References
Akyüz, M.H., Lee, C.Y.: Service level assignment and container routing for liner shipping service networks. Proceedings of the International MultiConference of Engineers and Computer Scientists 2 (2014)
Branchini, R.M., Armentano, V.A., Morabito, R.: Routing and fleet deployment in liner shipping with spot voyages. Transportation Research Part C: Emerging Technologies 57, 188–205 (2015)
Brouer, B.D., Alvarez, J.F., Plum, C.E.M., Pisinger, D., Sigurd, M.M.: A base integer programming model and benchmark suite for liner-shipping network design. Transportation Science 48(2), 281–312 (2014)
Brouer, B.D., Karsten, C.V., Pisinger, D.: Optimization in liner shipping. A Quarterly Journal of Operations Research 15(1), 1–35 (2017)
Christiansen, M., Fagerholt, K., Nygreen, B., Ronen, D.: Ship routing and scheduling in the new millennium. European Journal of Operational Research 228(3), 467–483 (2013)
Gelareh, S., Meng, Q.: A novel modeling approach for the fleet deployment problem within a short-term planning horizon. Transportation Research Part E: Logistics and Transportation Review 46(1), 76–89 (2010)
Guericke, S., Tierney, K.: Liner shipping cargo allocation with service levels and speed optimization. Transportation Research Part E: Logistics and Transportation Review 84, 40–60 (2015)
Karsten, C.V., Pisinger, D., Ropke, S., Brouer, B.D.: 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 (2015)
Meng, Q., Wang, T.: A chance constrained programming model for short-term liner ship fleet planning problems. Marit. Policy Manag. 37(4), 329–346 (2010)
Meng, Q., Wang, T., Wang, S.: Multi-period liner ship fleet planning with dependent uncertain container shipment demand. Marit. Policy Manag. 42(1), 43–67 (2013)
Petersen, B.: Shortest Path and Vehicle Routing, Ph.D. Thesis. DTU Management Engineering (2011)
Psaraftis, H.N., Kontovas, C.A.: Green maritime transportation: speed and route optimization. In: Psaraftis, H.N. (ed.) Green Transportation Logistics, International Series in OR & MS, vol. 226, pp. 299–349. Springer (2016)
Reinhardt, L.B., Plum, C.E., Pisinger, D., Sigurd, M.M., Vial, G.T.: The liner shipping berth scheduling problem with transit times. Transportation Research Part E: Logistics and Transportation Review 86, 116–128 (2016)
Stopford, M.: Maritime economics, 3rd edn. Routledge, London (2009)
United Nations Conference on Trade and Development: Review of maritime transport (2016)
Wang, H., Zhang, X., Wang, S.: A joint optimization model for liner container cargo assignment problem using state-augmented shipping network framework. Transportation Research Part C: Emerging Technologies 68, 425–446 (2016)
Wang, S., Meng, Q.: Liner ship fleet deployment with container transshipment operations. Transportation Research Part E: Logistics and Transportation Review 48(2), 470–484 (2012)
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Müller, D., Guericke, S., Tierney, K. (2017). Integrating Fleet Deployment into the Liner Shipping Cargo Allocation Problem. In: Bektaş, T., Coniglio, S., Martinez-Sykora, A., Voß, S. (eds) Computational Logistics. ICCL 2017. Lecture Notes in Computer Science(), vol 10572. Springer, Cham. https://doi.org/10.1007/978-3-319-68496-3_21
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DOI: https://doi.org/10.1007/978-3-319-68496-3_21
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