Green Voyage Planning: A Literature Survey on the Role of Sustainable Technologies and Strategies in Maritime Operations

• Autorzy: Fava Riccardo , Satta Giovanni

Identyfikatory

DOI

10.12716/1001.19.02.36

• Języki publikacji: EN

Abstrakty

EN

The rapid transition of the maritime sector toward emission-reduction goals set by international regulators leads to increasing pressure on the industry. Within this context, the present study aims to explore the potential impact of green technologies and strategies (GT&S) on voyage planning, a core process governed by IMO provisions, central to ensuring safe and sustainable navigation. The analysis highlighted current research gaps and proposed insights for future studies, with the aim of supporting the ongoing effort toward maritime decarbonization. In order to explore how GT&S may influence voyage planning, a targeted literature survey has been conducted. The selected contributions were grouped into six categories reflecting current technological and operational trends. Then, their potential impact on the components of voyage planning was assessed from a qualitative perspective. The survey suggests that all components are likely to be affected, introducing challenges which have been explored. The fact that most scholarly efforts appear to be primarily directed toward GT&S enabling short and medium-term sustainability reveals future research opportunities that cannot overlook the specificities of the shipping segment examined. The human element, in particular the role of masters and relevant stakeholders, also emerges as pivotal in managing this transition, supporting the need for further research focused on onboard operators.

Słowa kluczowe

EN

environment protection; MARPOL Annex VI; greenhouse gas emissions; Emission Control Areas; ECA; IMO GHG strategy; carbon neutrality; market-based measures; ETS; Emissions Trading System; decarbonization of shipping; International Maritime Organization

• Wydawca: Faculty of Navigation, Gdynia Maritime University
• Czasopismo: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
• Rocznik: 2025
• Tom: Vol. 19 No. 2
• Strony: 647--657
• Opis fizyczny: Bibliogr. 75 poz., rys., tab.

Twórcy

autor

Fava Riccardo

• University of Genova, Genova, Italy

• https://orcid.org/0009-0008-1207-5073

autor

Satta Giovanni

• University of Genova, Genova, Italy

• https://orcid.org/0000-0001-8717-7244

Bibliografia

• [1] Atilhan S., Park S., El-Halwagi M.M., Atilhan M.; Moore M., Nielsen R.B. Green hydrogen as an alternative fuel for the shipping industry. Current Opinion in Chemical Engineering 2021, 31:100668.
• [2] Babicz J., (2015). Wartsila encyclopedia of ship technology, second edition. Wartsila.
• [3] Bengue A.A., Alavi-Borazjani S.A., Chkoniya V., Cacho J.L.; Fiore M. Prioritizing Criteria for Establishing a Green Shipping Corridor Between the Ports of Sines and Luanda Using Fuzzy AHP. Sustainability 2024, 16, 9563.
• [4] Borén C.; Castells-Sanabra M.; Grifoll M. Proceedings of the Institution of Mechanical Engineers Part M: Journal of Engineering for the Maritime Environment. Proc IMechE Part M: J Engineering for the Maritime Environment 236(4).
• [5] Chen A., Chen W., Zheng J. Arctic Route Planning and Navigation Strategy: The Perspective of Ship Fuel Costs and Carbon Emissions. J. Mar. Sci. Eng. 2023, 11, 1308.
• [6] Chen S.-Y., Kern S., Li X.-Q., Hui F.-M., Ye Y.-F., Cheng X. Navigability of the Northern Sea Route for Arc7 ice-class vessels during winter and spring sea-ice conditions. Advances in Climate Change Research 13 (2022) 676e687.
• [7] Cheng L., Xu L., Bai X. Cargo selection, route planning, and speed optimization in tramp shipping under carbon intensity indicator (CII) regulations. Transportation Research Part E 194 (2025) 103948.
• [8] Christensen M., Georgati M., Arsanjani J.J. A risk-based approach for determining the future potential of commercial shipping in the Arctic. Journal of Marine Engineering & Technology 2022, VOL. 21, NO. 2, 82–99.
• [9] Dai L., Jing D., Hu H., Wang Z. An environmental and techno-economic analysis of transporting LNG via Arctic route. Transportation Research Part A 146 (2021) 56–71.
• [10] Di Lieto A., (2015). Bridge Resource Management: From the Costa Concordia to Navigation in the Digital Age. Part II and III. Hydeas Pty Ltd. ISBN: 978-0994267207.
• [11] Ding W., Wang Y., Dai L., Hu H. Does a carbon tax affect the feasibility of Arctic shipping? Transportation Research Part D 80 (2020) 102257.
• [12] DNV (2023). Maritime Forecast to 2050. A deep dive into shipping’s decarbonization journey. Energy transition outlook 2023.
• [13] Du W., Li Y., Shi J., Sun B., Wang C., Zhu B. Applying an improved particle swarm optimization algorithm to ship energy saving. Energy 263 (2023) 126080.
• [14] Fan A., Li Y., Liu H., Yang L., Tian Z., Li Y., Vladimir N. Development trend and hotspot analysis of ship energy management. Journal of Cleaner Production 389 (2023) 135899.
• [15] Gao J., Chi M., Hu Z. Energy Consumption Optimization of Inland Sea Ships Based on Operation Data and Ensemble Learning. Mathematical Problems in Engineering Volume 2022.
• [16] Gao J., Lan H., Zhang X., Iu H.H.C., Hong Y.-Y., Yin H. A coordinated generation and voyage planning optimization scheme for all-electric ships under emission policy. Electrical Power and Energy Systems 156 (2024) 109698.
• [17] Gao T., Tian J., Liu C., Huang C., Wu H.; Yuan Z. A model for speed and fuel refueling strategy of methanol dual-fuel liners with emission control areas. Transport Policy 161 (2025) 1–16.
• [18] Ghorbani M., Slaets P., Lacey J. Sensor-based modelling of suction sails to integrate into a numerical simulation tool for a wind-assisted vessel and its application to green shipping. Ocean Engineering 311 (2024) 118937.
• [19] Gospić I., Martić I., Degiuli N., Farkas A. Energetic and Ecological Effects of the Slow Steaming Application and Gasification of Container Ships. J. Mar. Sci. Eng. 2022, 10, 703.
• [20] Grandcolas S., (2022). A Metaheuristic Algorithm for Ship Weather Routing. Operations Research Forum.
• [21] Grifoll M., Borén C., Castells-Sanabra M. A comprehensive ship weather routing system using CMEMS products and A* algorithm. Ocean Engineering 255 (2022) 111427.
• [22] Guo Y., Wang Y., Chen Y., Wu L., Mao W. Learning-based Pareto-optimum routing of ships incorporating uncertain meteorological and oceanographic forecasts. Transportation Research Part E 192 (2024) 103786.
• [23] Guzelbulut C., Badalotti T., Fujita Y., Sugimoto T., Suzuki K. Artificial Neural Network-Based Route Optimization of a Wind-Assisted Ship. J. Mar. Sci. Eng. 2024, 12, 1645.
• [24] Havre H.F., Lien U., Ness M.M., Fagerholt K., Rødseth K.L. Network design with route planning for battery electric high-speed passenger vessel services. European Journal of Operational Research 315 (2024) 102–119.
• [25] He P., Jin J.G., Pan W., Chen J. Route, speed, and bunkering optimization for LNG-fueled tramp ship with alternative bunkering ports. Ocean Engineering 305 (2024) 117957.
• [26] Hein K., Xu Y., Wilson G., Gupta A.K. Coordinated Optimal Voyage Planning and Energy Management of All-Electric Ship with Hybrid Energy Storage System. IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 36, NO. 3, MAY 2021.
• [27] Hwang J.H., Kang D.W. Emission Control Routes in Liner Shipping between Korea and Japan. Mar. Sci. Eng. 2023, 11, 2250.
• [28] ICS (2022). Bridge Procedures Guide, sixth edition. Chapter 3. International Chamber of Shipping. ISBN: 978-1-913997-07-6.
• [29] IMO (1999). Guidelines for voyage planning. Resolution A.893(21).
• [30] IMO (2007). Adoption of the revised performance standards for integrated navigation systems (INS). Resolution MSC.252(83).
• [31] IMO (2023). 2023 IMO strategy on reduction of GHG emissions from ships. Resolution MEPC.377(80).
• [32] Jesus B., Ferreira I.A., Carreira A., Ove Erikstad S., Godina R. Economic framework for green shipping corridors: Evaluating cost-effective transition from fossil fuels towards hydrogen. International Journal of Hydrogen Energy 83 (2024) 1429–1447.
• [33] Johannessen J.A., Perrin A., Gaultier L., Herlédan S., Pouplin C., Collard F., Maze J.P., Dussauze M., Rapp J., Fanebust R., Andersen S., Franks O., Meyer R. Tools for optimizing performance of voyages at sea. TransNav, March 2021.
• [34] Jovic M., Tijan E., Brcic D., Pucihar A. Digitalization in Maritime Transport and Seaports: Bibliometric, Content and Thematic Analysis. J. Mar. Sci. Eng. 2022, 10, 486.
• [35] Karountzos O., Kagkelis G., Kepaptsoglou K. A Decision Support GIS Framework for Establishing Zero-Emission Maritime Networks: The Case of the Greek Coastal Shipping Network. Journal of Geovisualization and Spatial Analysis (2023) 7:16.
• [36] Kavirathna C.A., Shibasaki R., Ding W., Otsuka N. Feasibility of the Northern Sea route with the effect of emission control measures. Transportation Research Part D 123 (2023) 103896.
• [37] Klakeel T.M., Anantharaman M., Islma R., Garaniya V., (2023). Effectiveness of current technology in GHG reduction – a literature survey. The International Journal on Marine Navigation and Safety of Sea Transportation, volume 17 number 1.
• [38] Kuhlemann S., Tierney K. A genetic algorithm for finding realistic sea routes considering the weather. Journal of Heuristics (2020) 26:801–825.
• [39] Law, L.C., Foscoli, B., Mastorakos, E., Evans, S. A Comparison of Alternative Fuels for Shipping in Terms of Lifecycle Energy and Cost. Energies 2021, 14, 8502.
• [40] Li X., Sun B., Guo C., Du W., Li Y. Speed optimization of a container ship on a given route considering voluntary speed loss and emissions. Applied Ocean Research 94 (2020) 101995.
• [41] Li X., Sun B., Jin J., Ding J. Speed Optimization of Container Ship Considering Route Segmentation and Weather Data Loading: Turning Point-Time Segmentation Method. J. Mar. Sci. Eng. 2022, 10, 1835.
• [42] Li X., Lynch A.H. New insights into projected Arctic sea road: operational risks, economic values, and policy implications. Climatic Change (2023) 176:30.
• [43] Li Z., Wang K., Hua Y., Liu X., Ma R., Wang Z., Huang L. GA-LSTM and NSGA-III based collaborative optimization of ship energy efficiency for low-carbon shipping. Ocean Engineering 312 (2024) 119190.
• [44] Ma D., Zhou S., Han Y., Ma W., Huang H. Multi-objective ship weather routing method based on the improved NSGA-III algorithm. Journal of Industrial Information Integration 38 (2024) 100570.
• [45] Ma W., Ma D., Ma Y., Zhang J., Wang D. Green maritime: a routing and speed multi-objective optimization strategy. Journal of Cleaner Production 305 (2021) 127179.
• [46] Mannarini G., Salinas M.L., Carelli L., Petacco N., Orović J. VISIR-2: Ship weather routing in Python. Geosci. Model Dev., 17, 4355–4382, 2024.
• [47] Mason J., Larkin A., Bullock S., van der Kolk N., Broderick J.F., (2023a). Quantifying voyage optimisation with wind propulsion for short-term CO2 mitigation in shipping. Ocean Engineering 289 (2023) 116065
• [48] Mason J., Larkin A., Gallego-Schmid A., (2023b). Mitigating stochastic uncertainty from weather routing for ships with wind propulsion. Ocean Engineering 281 (2023) 114674
• [49] Nzualo T.D.N.M., de Oliveira C.E.F., Pérez T.O.A., González-Gorbeña E., Rosman P.C.C., Qassim R.Y.. Ship speed optimisation in green approach to tidal ports. Applied Ocean Research 115 (2021) 102845.
• [50] Perna A., Jannelli E., Di Micco S., Romano F., Minutillo M. Designing, sizing and economic feasibility of a green hydrogen supply chain for maritime transportation. Energy Conversion and Management 278 (2023) 116702.
• [51] Pfeifer A., Prebeg P., Duić N. Challenges and opportunities of zero emission shipping in smart islands: A study of zero emission ferry lines. eTransportation 3 (2020) 100048.
• [52] Poulsen R.T., Sampson H. A swift turnaround? Abating shipping greenhouse gas emissions via port call optimization. Transportation Research Part D 86 (2020) 102460.
• [53] Ryan C., Huang L., Li Z., Ringsberg J.W., Thomas G. An Arctic ship performance model for sea routes in ice-infested waters. Applied Ocean Research 117 (2021) 102950.
• [54] Shukla A., (2017). Literature review: an oblivious yet grounding task of research. Management Insight 13(1) 7 – 15.
• [55] Song Z., Zhang J., Tian W., Guedes Soares C. A multi-objective ship voyage optimisation method within sulfur emission control zones. Ocean Engineering 319 (2025) 120192.
• [56] Stopford M., (2008). Maritime Economics, third edition. Routledge, Taylor & Francis Group.
• [57] Sun W., Tang S., Liu X., Zhou S., Wei J. An Improved Ship Weather Routing Framework for CII Reduction Accounting for Wind-Assisted Rotors. J. Mar. Sci. Eng. 2022, 10, 1979.
• [58] Tillig F., Ringsberg J.W., Psaraftis H.N., Zis T. Reduced environmental impact of marine transport through speed reduction and wind assisted propulsion. Transportation Research Part D 83 (2020) 102380.
• [59] Tsai Y.-M., Lin C.-Y. Effects of the Carbon Intensity Index Rating System on the Development of the Northeast Passage. J. Mar. Sci. Eng. 2023, 11, 1341.
• [60] Wang H., Lang X., Mao W. Voyage optimization combining genetic algorithm and dynamic programming for fuel/emissions reduction. Transportation Research Part D 90 (2021) 102670.
• [61] Wang H., Liu Y., Jin Y., Wang S. Optimal Sailing Speeds and Time Windows in Inland Water Transportation Operations Management: Mathematical Models and Applications. Mathematics 2023, 11, 4747.
• [62] Wang K., Li J., Huang L., Ma R., Jiang X., Yuan Y., Mwero N.A., Negenborn R.R., Sun P., Yan X. A novel method for joint optimization of the sailing route and speed considering multiple environmental factors for more energy efficient shipping. Ocean Engineering 216 (2020) 107591.
• [63] Wang K., Xu H., Li J., Huang L., Ma R., Jiang X., Yuan Y., Mwero N.A., Sun P., Negenborn R.R., Yan X. A novel dynamical collaborative optimization method of ship energy consumption based on a spatial and temporal distribution analysis of voyage data. Applied Ocean Research 112 (2021) 102657.
• [64] Wang W., Liu Y., Zhen L., Wang H. How to Deploy Electric Ships for Green Shipping. J. Mar. Sci. Eng. 2022, 10, 1611.
• [65] Wang Z., Silberman J.A., Corbett J.J., (2021). Container vessels diversion pattern to trans-Arctic shipping routes and GHG emission abatement potential. Maritime Policy & Management, 48:4, 543-562.
• [66] Wang Z., Chen L., Wang B.; Huang L., Wang K., Ma R. Integrated optimization of speed schedule and energy management for a hybrid electric cruise ship considering environmental factors. Energy 282 (2023) 128795.
• [67] Xie X., Sun B., Li X., Zhao Y., Chen Y. Joint optimization of ship speed and trim based on machine learning method under consideration of load. Ocean Engineering 287 (2023) 11591
• [68] Xing H., Spence S., Chen H. A comprehensive review on countermeasures for CO2 emissions from ships. Renewable and Sustainable Energy Reviews 134 (2020) 110222.
• [69] Yang L., Chen G., Zhao J., Rytter N.G.M. Ship speed optimization considering ocean currents to enhance environmental sustainability in maritime shipping. Sustainability 2020, 12, 3649.
• [70] Yang Z., Qu W., Zhuo J. Optimization of Energy Consumption in Ship Propulsion Control under Severe Sea Conditions. J. Mar. Sci. Eng. 2024, 12, 1461.
• [71] Zhao S., Zhao S. Ship Global Traveling Path Optimization via a Novel Non-Dominated Sorting Genetic Algorithm. J. Mar. Sci. Eng. 2024, 12, 485.
• [72] Zhao W., Wang Y., Zhang Z., Wang H. Multicriteria ship route planning method based on improved particle swarm optimization–genetic algorithm. J. Mar. Sci. Eng. 2021, 9, 357.
• [73] Zhao X., Guo Y., Wang Y. Green maritime navigation: A multi-objective voyage optimization approach based on data-driven heuristics and emission awareness. Ocean Engineering 318 (2025) 120138.
• [74] Zhen L., Hu Z., Yan R., Zhuge D., Wang S. Route and speed optimization for liner ships under emission control policies. Transportation Research Part C 110 (2020) 330–345.
• [75] Zhou P., Zhou Z., Wang Y., Wang H. Ship Weather Routing Based on Hybrid Genetic Algorithm Under Complicated Sea Conditions. J. Ocean Univ. China (Oceanic and Coastal Sea Research) 2023 22: 28-42.

Uwagi

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