|Table of Contents|

Citation:
　He Zhang,Junfeng Dong,Siyuan Kong.Multi-Objective Dynamic Induction Research of Ship Routes in the Context of Low Carbon Shipping[J].Journal of Marine Science and Application,2025,(3):593-605.[doi:10.1007/s11804-024-00458-7]
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Multi-Objective Dynamic Induction Research of Ship Routes in the Context of Low Carbon Shipping

Info

Title:
Multi-Objective Dynamic Induction Research of Ship Routes in the Context of Low Carbon Shipping
Author(s):
He Zhang;  Junfeng Dong;  Siyuan Kong
Affilations:
Author(s):
He Zhang;  Junfeng Dong;  Siyuan Kong
College of Transportation Engineering, Dalian Maritime University, Dalian, 116026, China
Keywords:
Dynamic route induction; Low-carbon shipping; Short-term vessel flow prediction; Multi-objective induction model; Maritime transport efficiency
分类号:
-
DOI:
10.1007/s11804-024-00458-7
Abstract:
To improve the efficiency of ship traffic in frequently traded sea areas and respond to the national “dual-carbon” strategy, a multi-objective ship route induction model is proposed. Considering the energy-saving and environmental issues of ships, this study aims to improve the transportation efficiency of ships by providing a ship route induction method. Ship data from a certain bay during a defined period are collected, and an improved backpropagation neural network algorithm is used to forecast ship traffic. On the basis of the forecasted data and ship route induction objectives, dynamic programming of ship routes is performed. Experimental results show that the routes planned using this induction method reduce the combined cost by 17.55% compared with statically induced routes. This method has promising engineering applications in improving ship navigation efficiency, promoting energy conservation, and reducing emissions.

References:

[1] Ahmed T, Sankar S, Sandhya M (2021) Multi-objective optimal medical data informatics standardization and processing technique for telemedicine via machine learning approach. Journal of Ambient Intelligence and Humanized Computing 12(5): 5349-5358. DOI: 10.1007/s12652-020-02016-9
[2] Cao YH (2010) Research on ship trajectory planning method based on particle swarm optimization algorithm. Master thesis, Fudan University, Shanghai, 37-45.
[3] Chen SY, Shao ZP, Fang XL, Shao CF (2001) Research on the simulation model of traffic flow in harbor waterways. Journal of Dalian Maritime University 27(1): 34-38. DOI: 10.16411/j.cnki.issn1006-7736.2001.01.008
[4] De A, Choudhary A, Tiwari MK (2019) Multiobjective approach for sustainable ship routing and scheduling with draft restrictions. IEEE Transactions on Engineering Management 66(1): 35-51. DOI: 10.1109/TEM.2017.2766443
[5] De A, Wang JW, Tiwari MK (2020) Hybridizing basic variable neighborhood search with particle swarm optimization for solving sustainable ship routing and bunker management problem. IEEE Transactions on Intelligent Transportation Systems 21(3): 986-997. DOI: 10.1109/TITS.2019.2900490
[6] De AR, Wang JW, Tiwari MK (2021) Fuel bunker management strategies within sustainable container shipping operation considering disruption and recovery policies. IEEE Transactions on Engineering Management 68(4): 1089-1111. DOI: 10.1109/TEM.2019.2923342
[7] Dong HC (2020) Research on traffic state discrimination and short-time traffic flow prediction method based on deep learning. Master thesis, Beijing Jiaotong University, Beijing, 21-28.
[8] Du S, Liu YH, Chen X (2018) Open water sailing vessel route planning based on genetic algorithm. Journal of Shanghai Maritime University 39(2): 1-6. DOI: 10.13340/j.jsmu.2018.02.001.
[9] Huang DM, Yang J, He SQ (2018) Research on route planning of improved A* algorithm based on weights. Marine Information 33(2): 16-22. DOI: 10.19661/j.cnki.mi.2018.02.004
[10] James M, Alice L, Alejandro GS (2023) Mitigating stochastic uncertainty from weather routing for ships with wind propulsion Ocean Engineering 281(1): 1-15. https://doi.org/10.1016/j.oceaneng.2023.114674
[11] Li LZ, Ji B, Yu SS (2022) Branch-and-price algorithm for the tramp ship routing and scheduling problem considering ship speed and payload. Journal of Marine Science and Engineering 10(12): 1-16. https://doi.org/10.3390/jmse10121811
[12] Li M, Xie XL, Pan W (2019) Application of traffic guidance concept in shipping-concept and composition of ship navigation guidance system. World Maritime Transport 42(7): 29-32. DOI: 10.16176/j.cnki.21-1284.2019.07.007
[13] Liu RW, Chen J, Liu Z (2017) Vessel traffic flow separation-prediction using low-rank and sparse decomposition. IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), Yokohama, 1-6. DOI: 10.1109/ITSC.2017.8317741
[14] Liu Y, Xie XL, He A (2019) Ship route planning in continuous construction waters. China Navigation 42(3): 51-54
[15] Liu ZY, Zhou CH, Zhao JN (2021) Modelling and simulation of channel passing capacity based on metacellular automata. Journal of System Simulation 33(10): 2478-2487. DOI: 10.16182/j.issn1004731x.joss.20-0587
[16] Lv C, Cui M, Wu G (2022) Ship route planning method for polar regions based on Dijkstra’s algorithm. Ship Engineering 44(6): 10-19. https://kns.cnki.net/kcms2
[17] Ma YH, Qiang YR, Yang M (2020) A time series forecasting method based on empirical modal decomposition. Journal of Northwest Normal University (Natural Science Edition) 56(1): 27-34. DOI: 10.16783/j.cnki.nwnuz.2020.01.004
[18] Neumann T (2015) Good choice of transit vessel route using Dempster-Shafer theory. International Siberian Conference on Control and Communications (SIBCON), Omsk, 1-4. DOI: 10.1109/SIBCON.2015.7146964
[19] Shao CF, Fang XL (2002) Fluid modelling of ship traffic flow. Journal of Dalian Maritime University 28(1): 52-55. DOI: 10.16411/j.cnki.issn1006-7736.2002.01.014
[20] Tsou MC, Kao SL, Su CM (2010) Decision support from genetic algorithms for ship collision avoidance route planning and alerts. Journal of Navigation 63(1): 167. https://doi.org/10.1017/S037346330999021X
[21] UNCTAD secretariat (2022) Trade geography and supply chain reconfiguration: Implications for trade, global value chains and maritime transport. Geneva, Report No. TD/B/C.I/54
[22] Umit G (2023) Estimating bulk carriers’ main engine power andemission. Brodogradnja 74(1): 85-98. https://doi.org/10.21278/brod74105
[23] Yang X, Li K, Chen WB (2013) Research on modelling and simulation of inland ship traffic flow. China Navigation 36(3): 80-85. https://kns.cnki.net/kcms2
[24] Zhao HC (2017) Design of dynamic route planning method based on real weather. Master thesis, Harbin Engineering University, Harbin, 12-19.
[25] Zhu J (2010) Traffic time impedance model based on ship flow. Journal of Wuhan University of Technology (Transportation Science and Engineering Edition) 34(3): 591-594. https://kns.cnki.net/kcms2

Memo

Memo:
Received date:2023-8-28;Accepted date:2024-3-27。
Foundation item:Supported by the National Key R&D Program of China project (2017YFC0805309) and the National Natural Science Foundation of China (60602020).
Corresponding author:He Zhang,E-mail:zhanghe@dlmu.edu.cn
Last Update: 2025-05-28