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Among the spectrum of logistics-based measures for green maritime transportation, this chapter focuses on speed optimization. This involves the selection of an appropriate speed by the vessel, so as to optimize a certain objective. As ship speed is not fixed, depressed shipping markets and/or high fuel prices induce slow steaming which is being practised in many sectors of the shipping industry. In recent years the environmental dimension of slow steaming has also become important, as ship emissions are directly proportional to fuel burned. Win-win solutions are sought, but they will not necessarily be possible. The chapter presents some basics, discusses the main trade-offs and also examines combined speed and route optimization problems. Some examples are finally presented so as to highlight the main issues that are at play.
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Aas, B., Gribkovskaia, I., Halskau, Ø., Sr., & Shlopak, A. (2007). Routing of supply vessels to petroleum installations. International Journal of Physical Distribution & Logistics Management, 37(2), 164–179. CrossRef
Agarwal, R., & Ergun, Ö. (2008). Ship scheduling and network design for cargo routing in liner shipping. Transportation Science, 42(2), 175–196. CrossRef
Alderton, P. M. (1981). The optimum speed of ships. Journal of Navigation, 34, 341–355. CrossRef
Alphaliner. (2013, October). Extra and super slow steaming help absorb 7.4 % of fleet. Alphaliner Weekly Newsletter, 2013(44).
Alvarez, J. (2009). Joint routing and deployment of a fleet of container vessels. Maritime Economics & Logistics, 11, 186–208. CrossRef
Alvarez, J. F., Tsilingiris, P., Engebrethsen, E. S., & Kakalis, N. M. (2011). Robust fleet sizing and deployment for industrial and independent bulk ocean shipping companies. INFOR: Information Systems and Operational Research, 49(2), 93–107.
Andersson, H., Duesund, J. M., & Fagerholt, K. (2011). Ship routing and scheduling with cargo coupling and synchronization constraints. Computers & Industrial Engineering, 61(4), 1107–1116. CrossRef
Andersson, H., Fagerholt, K., & Hobbesland, K. (2014). Integrated maritime fleet deployment and speed optimization: Case study from RoRo shipping. Computers & Operations Research, 55, 233–240. CrossRef
Barrass, C. B. (2005). Ship design and performance for masters and mates. Oxford: Butterworth-Heinemann.
Bausch, D., Brown, G., & Ronen, D. (1998). Scheduling short-term marine transport of bulk products. Maritime Policy and Management, 25, 335–348. CrossRef
Benford, H. (1981). A simple approach to fleet deployment. Maritime Policy & Management, 8, 223–228. CrossRef
Brouer, B. D., Alvarez, J. F., Plum, C. E., Pisinger, D., & Sigurd, M. M. (2013). A base integer programming model and benchmark suite for liner-shipping network design. Transportation Science, 48(2), 281–312. CrossRef
Brown, G., Graves, G., & Ronen, D. (1987). Scheduling ocean transportation of crude oil. Management Science, 33, 335–346. CrossRef
Cariou, P. (2011). Is slow steaming a sustainable means of reducing CO 2 emissions from container shipping? Transportation Research Part D, 16(3), 260–264. CrossRef
Cariou, P., & Cheaitou, A. (2012). The effectiveness of a European speed limit versus an international bunker-levy to reduce CO 2 emissions from container shipping. Transportation Research Part D, 17, 116–123. CrossRef
CBO. (2006). The economic costs of disruptions in container shipments. Washington, DC: U.S. Congress, Congressional Budget Office.
Chang, C. C., & Wang, C. M. (2014). Evaluating the effects of speed reduce for shipping costs and CO 2 emission. Transportation Research Part D: Transport and Environment, 31, 110–115. CrossRef
Christiansen, M., Fagerholt, K., Nygreen, B., & Ronen, D. (2007). Maritime transportation. In C. Barnhart & G. Laporte (Eds.), Transportation, handbooks in operations research and management science (Vol. 14, pp. 189–284). Amsterdam: Elsevier.
Christiansen, M., Fagerholt, K., Nygreen, B., Ronen, D. (2013). Ship routing and scheduling in the new millennium. European Journal of Operational Research 228, 467–483.
Christiansen, M., Fagerholt, K., & Ronen, D. (2004). Ship routing and scheduling: Status and perspectives (review). Transportation Science, 38(1), 1–18. CrossRef
Corbett, J., Wang, H., & Winebrake, J. (2010). The effectiveness and costs of speed reductions on emissions from international shipping. Transportation Research Part D: Transport and Environment, 14, 593–598. CrossRef
Cordeau, J.-F., Laporte, G., Legato, P., & Moccia, L. (2005). Models and tabu search heuristics for the berth-allocation problem. Transportation Science, 39(4), 526–538. CrossRef
Devanney, J. W. (2007). Solving elastic transportation networks. Center for Tankship Excellence. Retrieved from www.c4tx.org
Devanney, J. W. (2010, October). The impact of bunker price on VLCC spot rates. Proceedings of the 3rd International Symposium on Ship Operations, Management and Economics. SNAME Greek Section, Athens, Greece.
Devanney, J. W. (2011). The impact of charter party speeds on CO 2 emissions. Center for Tankship Excellence. Retrieved from www.c4tx.org
Doudnikoff, M., & Lacoste, R. (2014). Effect of a speed reduction of containerships in response to higher energy costs in sulphur emission control areas. Transportation Research Part D: Transport and Environment, 27, 19–29. CrossRef
Du, Y., Chen, Q., Quan, X., Long, L., & Fung, R. Y. K. (2011). Berth allocation considering fuel consumption and vessel emissions. Transportation Research Part E, 47, 1021–1037. CrossRef
Eefsen, T., & Cerup-Simonsen, B. (2010, July). Speed, carbon emissions and supply chain in container shipping. Proceedings of the Annual Conference of the International Association of Maritime Economists, IAME 2010, Lisbon, Portugal.
Faber, J., Freund, M., Köpke, M., & Nelissen, D. (2010). Going slow to reduce emissions: Can the current surplus of maritime transport capacity be turned into an opportunity to reduce GHG emissions? Seas at Risk.
Fagerholt, K. (2001). Ship scheduling with soft time windows—An optimization based approach. European Journal of Operational Research, 131, 559–571. CrossRef
Fagerholt, K., Gausel, N., Rakke, J., & Psaraftis, H. (2015). Maritime routing and speed optimization with emission control areas. Transportation Research Part C: Emerging Technologies, 52, 57–73. CrossRef
Fagerholt, K., Laporte, G., & Norstad, I. (2010). Reducing fuel emissions by optimizing speed on shipping routes. Journal of the Operational Research Society, 61, 523–529. CrossRef
Fagerholt, K., & Ronen, D. (2013). Bulk ship routing and scheduling: Solving practical problems may provide better results. Maritime Policy & Management, 40(1), 48–64. CrossRef
Gkonis, K. G., & Psaraftis, H. N. (2012, October). Modelling tankers’ optimal speed and emissions. Proceedings SNAME 2012 Annual Meeting, Providence, RI.
Goodchild, A. V., & Daganzo, C. F. (2007). Crane double cycling in container ports: Planning methods and evaluation. Transportation Research Part B: Methodological, 41(8), 875–891. CrossRef
Grønhaug, R., Christiansen, M., Desaulniers, G., & Desrosiers, J. (2010). A branch-and-price method for a liquefied natural gas inventory routing problem. Transportation Science, 44(3), 400–415. CrossRef
Halvorsen-Weare, E. E., & Fagerholt, K. (2011). Robust supply vessel planning. In J. Pahl, T. Reiners, & S. Voß (Eds.), Network optimization (pp. 559–573). Heidelberg: Springer. CrossRef
Halvorsen-Weare, E. E., & Fagerholt, K. (2013). Routing and scheduling in a liquefied natural gas shipping problem with inventory and berth constraints. Annals of Operations Research, 203(1), 167–186. CrossRef
Hsu, C. I., & Hsieh, Y. P. (2005). Direct versus terminal routing on a maritime hub-and-spoke container network. Journal of Marine Science and Technology, 13(3), 209–217.
Hvattum, L. M., Norstad, I., Fagerholt, K., & Laporte, G. (2013). Analysis of an exact algorithm for the vessel speed optimization problem. Networks, 62(2), 132–135. CrossRef
Hwang, H.-S., Visoldilokpun, S., & Rosenberger, J. M. (2008). A branch-and-price-and-cut method for ship scheduling with limited risk. Transportation Science, 42(3), 336–351. CrossRef
IMO. (2009). Second IMO GHG study 2009—doc. MEPC59/INF.10. London: International Maritime Organization (IMO).
IMO. (2014, June). Third IMO GHG Study 2014, Co-authored by Smith, T. W. P., Jalkanen, J. P., Anderson, B. A., Corbett, J. J., Faber, J., Hanayama, S., et al. London: International Maritime Organization (IMO).
Imai, A., Shintani, K., Papadimitriou, S. (2009). Multi-port vs. Hub-and-Spoke port calls by containerships. Transportation Research Part E 45, 740–757.
Jetlund, A. S., & Karimi, I. A. (2004). Improving the logistics of multi-compartment chemical tankers. Computers & Chemical Engineering, 28(8), 1267–1283. CrossRef
Kapetanis, G. N., Gkonis, K., & Psaraftis, H. N. (2014, April). Estimating the operational effects of a bunker levy: The case of handymax bulk carriers. TRA 2014 conference, Paris, France.
Kontovas, C. A., & Psaraftis, H. N. (2011). Reduction of emissions along the maritime intermodal container chain. Maritime Policy & Management, 38(4), 455–473. CrossRef
Lang, N., & Veenstra, A. (2010). A quantitative analysis of container vessel arrival planning strategies. OR Spectrum, 32, 477–499. CrossRef
Lin, D.-Y., & Liu, H.-Y. (2011). Combined ship allocation, routing and freight assignment in tramp shipping. Transportation Research Part E: Logistics and Transportation Review, 47(4), 414–431. CrossRef
Lindstad, H., Asbjørnslett, B. E., & Strømman, A. H. (2011). Reductions in greenhouse gas emissions and cost by shipping at lower speeds. Energy Policy, 39(6), 3456–3464. CrossRef
Lloyds List. (2009, November 16). CKYH carriers agree to super-slow steaming. Lloyds List.
Lo, H. K., & McCord, M. R. (1998). Adaptive ship routing through stochastic ocean currents: General formulations and empirical results. Transportation Research Part A: Policy and Practice, 32(7), 547–561.
Maersk. (2013). Building the world’s biggest ship. Retrieved from http://www.maersk.com/innovation/leadingthroughinnovation/pages/buildingtheworldsbiggestship.aspx
Magirou, E. F., Psaraftis, H. N., & Bouritas, T. (2015). The economic speed of an oceangoing vessel in a dynamic setting. Transportation Research Part B, 76, 48–67.
Meng, Q., & Wang, S. (2011). Optimal operating strategy for a long-haul liner service route. European Journal of Operational Research, 215, 105–114. CrossRef
Meng, Q., Wang, S., Andersson, H., & Thun, K. (2013). Containership routing and scheduling in liner shipping: overview and future research directions. Transportation Science, 48(2), 265–280. CrossRef
Mills, J., Donnison, A., & Brightwell, G. (2014). Factors affecting microbial spoilage and shelf-life of chilled vacuum-packed lamb transported to distant markets: A review. Meat Science, 98(1), 71–80. CrossRef
Moccia, L., Cordeau, J. F., Gaudioso, M., & Laporte, G. (2006). A branch‐and‐cut algorithm for the quay crane scheduling problem in a container terminal. Naval Research Logistics, 53(1), 45–59. CrossRef
Norlund, E. K., Gribkovskaia, I. (2013). Reducing emissions through speed optimization in supply vessel operations, Transportation Research Part D 23, 105–113.
Norstad, I., Fagerholt, K., & Laporte, G. (2011). Tramp ship routing and scheduling with speed optimization. Transportation Research Part C, 19, 853–865. CrossRef
Notteboom, T. E., & Vernimmen, B. (2010). The effect of high fuel costs on liner service configuration in container shipping. Journal of Transport Geography, 17, 325–337. CrossRef
Perakis, A. N. (1985). A second look at fleet deployment. Maritime Policy & Management, 12, 209–214. CrossRef
Perakis, A. N., & Jaramillo, D. I. (1991). Fleet deployment optimization for liner shipping. Part 1: Background, problem formulation and solution approaches. Maritime Policy & Management, 18(3), 183–200. CrossRef
Perakis, A. N., & Papadakis, N. A. (1987a). Fleet deployment models, part 1. Maritime Policy & Management, 14, 127–144. CrossRef
Perakis, A. N., & Papadakis, N. A. (1987b). Fleet deployment models part 2. Maritime Policy & Management, 14, 145–155. CrossRef
Perakis, A. N., & Papadakis, N. A. (1989). Minimal time vessel routing in a time-dependent environment. Transportation Science, 23(4), 266–276. CrossRef
Powell, B. J., & Perakis, A. N. (1997). Fleet deployment optimization for liner shipping: An integer programming model. Maritime Policy & Management, 24(2), 183–192. CrossRef
Psaraftis, H. N. (2011). A multi-commodity, capacitated pickup and delivery problem: The single and two-vehicle cases, European Journal of Operational Research 215, 572–580.
Psaraftis, H. N. (2012). Market based measures for greenhouse gas emissions from ships. WMU Journal of Maritime Affairs. doi: 10.1007/s13437-012-0030-5.
Psaraftis, H. N., & Kontovas, C. A. (2009a). CO 2 emissions statistics for the world commercial fleet. WMU Journal of Maritime Affairs, 8(1), 1–25. CrossRef
Psaraftis, H. N., & Kontovas, C. A. (2009b, May 26–29). Ship emissions: Logistics and other tradeoffs. Proceedings of 10th International Marine Design Conference, Trondheim, Norway.
Psaraftis, H. N., & Kontovas, C. A. (2010). Balancing the economic and environmental performance of maritime transportation. Transportation Research Part D, 15(8), 458–462. CrossRef
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. CrossRef
Psaraftis, H. N., & Kontovas, C. A. (2014). Ship speed optimization: Concepts, models and combined speed-routing scenarios. Transportation Research Part C: Emerging Technologies, 44, 52–69. CrossRef
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 transportation logistics: Making global supply chains effective. Cham, Switzerland: Springer.
Qi, X., & Song, D.-P. (2012). Minimizing fuel emissions by optimizing vessel schedules in liner shipping with uncertain port times. Transportation Research Part E: Logistics and Transportation Review, 48(4), 863–880. CrossRef
Rana, K., & Vickson, R. G. (1991). Routing container ships using Lagrangian relaxation and decomposition. Transportation Science, 25(3), 201–214. CrossRef
Reinhardt, L. B., & Pisinger, D. (2014). A branch and cut algorithm for the container shipping network design problem. Flexible Services and Manufacturing Journal, 24(3), 349–374. CrossRef
Ronen, D. (1982). The effect of oil price on the optimal speed of ships. Journal of the Operational Research Society, 33, 1035–1040. CrossRef
Ronen, D. (2011). The effect of oil price on containership speed and fleet size. Journal of the Operational Research Society, 62(1), 211–216. CrossRef
Song, D. P., & Xu, J. J. (2012). CO2 emission comparison between direct and feeder liner services: A case study of Asia-Europe services interfacing with the UK. International Journal of Sustainable Transportation, 6(4), 214–237. CrossRef
Stahlbock, R., & Voß, S. (2008). Operations research at container terminals: A literature update. OR Spectrum, 30(1), 1–52. CrossRef
Stopford, M. (2009). Maritime economics, Third Edition, Routledge, Taylor and Francis, London and New York.
Tirado, G., Hvattum, L. M., Fagerholt, K., & Cordeau, J.-F. (2013). Heuristics for dynamic and stochastic routing in industrial shipping. Computers & Operations Research, 40(1), 253–263. CrossRef
TradeWinds. (2009, October 30). Maersk insists on slow speeds. TradeWinds Magazine.
TradeWinds. (2010, December 13). Slow spur for Maersk VLCCs. TradeWinds Magazine
Ulysses. (2012). EU FP7 project Ulysses web site. Retrieved from http://www.ultraslowships.com/index.html
Wang, S., & Meng, Q. (2012a). Sailing speed optimization for container ships in a liner shipping network. Transportation Research Part E, 48(3), 701–714. CrossRef
Wang, S., & Meng, Q. (2012b). Liner ship route schedule design with sea contingency time and port time uncertainty. Transportation Research Part B, 46(5), 615–633. CrossRef
Wang, S., & Meng, Q. (2012c). Robust schedule design for liner shipping services. Transportation Research Part E, 48, 1093–1106. CrossRef
Wang, S., Meng, Q., & Liu, Z. (2013a). Bunker consumption optimization methods in shipping: A critical review and extensions. Transportation Research Part E: Logistics and Transportation Review, 53, 49–62. CrossRef
Wang, S., Meng, Q., & Liu, Z. (2013b). A note on “Berth allocation considering fuel consumption and vessel emissions”. Transportation Research Part E, 49, 48–54. CrossRef
Wang, S., Alharbi, A., Davy, P. (2014). Liner ship route schedule design with port time windows. Transportation Research Part C 41, 1–17.
Yao, Z., Ng, S. H., & Lee, L. H. (2012). A study on bunker fuel management for the shipping liner services. Computers & Operations Research, 39(5), 1160–1172. CrossRef
Zeng, Q., & Yang, Z. (2007). Model integrating fleet design and ship routing problems for coal shipping. In Computational science–ICCS 2007 (pp. 1000–1003). Heidelberg: Springer. CrossRef
- Green Maritime Transportation: Speed and Route Optimization
Harilaos N. Psaraftis
Christos A. Kontovas
- Chapter 9
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