102
GPU acceleration, cloud-native clusters, or hybrid
models—will yield the best result. Thus, the selection
of suitable techniques requires analyzing and
comparing these approaches. That analysis demands
profound domain knowledge and strong
programming skills. Despite these hurdles, multi-
objective HPC methods can minimize fuel use, boost
safety, and lower the environmental impact. With
greater HPC availability and increasing computational
demands for algorithms, these methods might gain
broader use in weather-based ship routing. The MOO-
SWR drive for efficiency, safety, and sustainability will
spur further innovation in weather-based routing.
Addressing these challenges and exploring diverse
HPC strategies, researchers can build efficient models
based on HPC to resolve difficult trade-offs in high-
demand computational domains, such as maritime
domains, in general and particularly for ship weather
routing.
Future work will include searching for a validated
unified HPC-based multi-objective ship routing
framework that better matches real-world scenarios,
enabling quick responses under actual conditions. The
primary objective is to develop a highly efficient and
adaptable ship weather routing method capable of
handling large-scale environmental datasets and
rapidly updating route plans in response to changing
conditions, thereby ensuring reliable performance in
time-critical, real-time scenarios.
REFERENCES
[1] S. Deng and Z. Mi, “A review on carbon emissions of
global shipping,” Mar. Dev., vol. 1, no. 1, pp. 1–10, 2023,
doi: 10.1007/s44312-023-00001-2.
[2] ShipUniverse, “Top 30 Reasons Why Maritime Shipping
Is the Backbone of Global Trade,” 2024.
[3] J. Verschuur, E. E. Koks, and J. W. Hall, “Ports’ criticality
in international trade and global supply-chains.”
[4] Statista, “Breakdown of CO$_2$ emissions in the
transportation sector worldwide 2020, by subsector,”
2021. [Online]. Available:
https://www.statista.com/statistics/1185535/transport-
carbon-dioxide-emissions-breakdown/
[5] W. Shao, P. Zhou, and S. K. Thong, “Development of a
novel forward dynamic programming method for
weather routing,” J. Mar. Sci. Technol., vol. 17, no. 2, pp.
239–251, Jun. 2012, doi: 10.1007/s00773-011-0152-z.
[6] L. P. Perera and C. G. Soares, “Weather routing and safe
ship handling in the future of shipping,” Ocean Eng., vol.
130, pp. 684–695, 2017, doi:
10.1016/j.oceaneng.2016.09.007.
[7] L. Walther, A. Rizvanolli, M. Wendebourg, and C. Jahn,
“Modeling and Optimization Algorithms in Ship
Weather Routing,” Int. J. e-Navigation Marit. Econ., vol.
4, pp. 31–45, Jun. 2016, doi: 10.1016/j.enavi.2016.06.004.
[8] J. Szlapczynska and R. Szlapczynski, “Preference-based
evolutionary multi-objective optimization in ship
weather routing,” Appl. Soft Comput. J., vol. 84, Nov.
2019, doi: 10.1016/j.asoc.2019.105742.
[9] E. G. Talbi, M. Basseur, A. J. Nebro, and E. Alba, “Multi-
objective optimization using metaheuristics: Non-
standard algorithms,” Int. Trans. Oper. Res., vol. 19, no.
1–2, pp. 283–305, Jan. 2012, doi: 10.1111/j.1475-
3995.2011.00808.x.
[10] P. Czarnul, J. Proficz, and K. Drypczewski, “Survey of
Methodologies, Approaches, and Challenges in Parallel
Programming Using High-Performance Computing
Systems,” 2020, Hindawi Limited. doi:
10.1155/2020/4176794.
[11] Ü. Öztürk, M. Akdağ, and T. Ayabakan, “A review of
path planning algorithms in maritime autonomous
surface ships: Navigation safety perspective,” May 01,
2022, Elsevier Ltd. doi: 10.1016/j.oceaneng.2022.111010.
[12] K. SKÓRA and A. WOLSKI, “VOYAGE PLANNING,”
Sci. J. Silesian Univ. Technol. Ser. Transp., vol. 92, pp.
123–128, Sep. 2016, doi: 10.20858/sjsutst.2016.92.12.
[13] James and Richard W, Application of wave forecasts to
marine navigation. New York University, 1957.
[14] Hagiwara and Hideki, “Weather routing of (sail-
assisted) motor vessels.,” Technische Universiteit Delft,
1989.
[15] Y. H. Lin, M. C. Fang, and R. W. Yeung, “The
optimization of ship weather-routing algorithm based on
the composite influence of multi-dynamic elements,”
Appl. Ocean Res., vol. 43, pp. 184–194, 2013, doi:
10.1016/j.apor.2013.07.010.
[16] Y. Chen, W. Tian, and W. Mao, “Strategies to improve
the isochrone algorithm for ship voyage optimisation,”
Ships Offshore Struct., 2024, doi:
10.1080/17445302.2024.2329011.
[17] D. Sen and C. P. Padhy, “An approach for development
of a ship routing algorithm for application in the North
Indian Ocean region,” Appl. Ocean Res., vol. 50, pp. 173–
191, 2015, doi: 10.1016/j.apor.2015.01.019.
[18] K. Takashima, B. Mezaoui, and R. Shoji, “On the fuel
saving operation for coastal merchant ships using
weather routing,” Mar. Navig. Saf. Sea Transp., vol. 3, no.
4, pp. 431–436, 2009, doi: 10.1201/9780203869345.ch75.
[19] M. Zyczkowski and R. Szlapczynski, “Collision risk-
informed weather routing for sailboats,” Reliab. Eng.
Syst. Saf., vol. 232, no. November 2022, p. 109015, 2023,
doi: 10.1016/j.ress.2022.109015.
[20] C. U. Bottner, “Weather routing for ships in degraded
condition,” in Proceedings of the International
Symposium on Maritime Safety, Security and
Environmental Protection. Athens, Greece, 2007.
[21] S. Calvert, E. Deakins, and R. Motte, “A Dynamic System
for Fuel Optimization Trans-Ocean,” J. Navig., vol. 44, no.
2, pp. 233–265, 1991, doi: 10.1017/S0373463300009978.
[22] C. de Wit, “Proposal for Low Cost Ocean Weather
Routeing,” J. Navig., vol. 43, no. 3, pp. 428–439, 1990, doi:
10.1017/S0373463300014053.
[23] H. Wang, W. Mao, and L. Eriksson, “A Three-
Dimensional Dijkstra’s algorithm for multi-objective ship
voyage optimization,” Ocean Eng., vol. 186, no. June, p.
106131, 2019, doi: 10.1016/j.oceaneng.2019.106131.
[24] J. Yang, L. Wu, and J. Zheng, “Multi-Objective Weather
Routing Algorithm for Ships: The Perspective of Shipping
Company’s Navigation Strategy,” J. Mar. Sci. Eng., vol.
10, no. 9, 2022, doi: 10.3390/jmse10091212.
[25] W. Zhao, H. Wang, J. Geng, W. Hu, Z. Zhang, and G.
Zhang, “Multi-Objective Weather Routing Algorithm for
Ships Based on Hybrid Particle Swarm Optimization,” J.
Ocean Univ. China, vol. 21, no. 1, pp. 28–38, 2022, doi:
10.1007/s11802-022-4709-8.
[26] R. Dębski and R. Dreżewski, “Multi-Objective Ship
Route Optimisation Using Estimation of Distribution
Algorithm,” Appl. Sci., vol. 14, no. 13, 2024, doi:
10.3390/app14135919.
[27] X. Li, H. Wang, and Q. Wu, “Multi-objective
optimization in ship weather routing,” 2017 Constr.
Nonsmooth Anal. Relat. Top. (Dedicated to Mem. V.F.
Demyanov), CNSA 2017 - Proc., pp. 1–4, 2017, doi:
10.1109/CNSA.2017.7973982.
[28] R. Szlapczynski, J. Szlapczynska, and R. Vettor, “Ship
weather routing featuring w-MOEA/D and uncertainty
handling,” Appl. Soft Comput., vol. 138, p. 110142, 2023,
doi: 10.1016/j.asoc.2023.110142.
[29] R. Szlapczynski and J. Szlapczynska, “W-dominance:
Tradeoff-inspired dominance relation for preference-
based evolutionary multi-objective optimization,”
Swarm Evol. Comput., vol. 63, no. March 2020, p. 100866,
2021, doi: 10.1016/j.swevo.2021.100866.