TY - JOUR
T1 - Hybridizing basic variable neighborhood search with particle swarm optimization for solving sustainable ship routing and bunker management problem
AU - De, Arijit
AU - Wang, Junwei
AU - Tiwari, Manoj Kumar
N1 - Funding Information:
Manuscript received December 2, 2017; revised August 17, 2018 and October 29, 2018; accepted February 16, 2019. Date of publication March 15, 2019; date of current version February 28, 2020. This work was supported in part by the National Natural Science Foundation of China under Grant 71571156, in part by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China, under Grant T32-101/15-R, in part by The University of Hong Kong through the Seed Fund for Basic Research under Grant 201611159213, and in part by the Open Project funded by State Key Laboratory of Synthetical Automation for Process Industries under Grant PAL-N201802. The Associate Editor for this paper was E. Kaisar. (Corresponding author: Junwei Wang.) A. De is with the Newcastle University Business School, Newcastle University, Newcastle upon Tyne NE1 7RU, U.K., and also with the Shenzhen Institute of Research and Innovation, The University of Hong Kong, Hong Kong (e-mail: [email protected]).
Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant 71571156, in part by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China, under Grant T32-101/15-R, in part by The University of Hong Kong through the Seed Fund for Basic Research under Grant 201611159213, and in part by the Open Project funded by State Key Laboratory of Synthetical Automation for Process Industries under Grant PAL-N201802.
Publisher Copyright:
© 2000-2011 IEEE.
PY - 2020/3
Y1 - 2020/3
N2 - This paper studies a novel sustainable ship routing problem considering a time window concept and bunker fuel management. Ship routing involves the decisions corresponding to the deployment of vessels to multiple ports and time window concept helps to maintain the service level of the port. Reducing carbon emissions within the maritime transportation domain remains one of the most significant challenges as it addresses the sustainability aspect. Bunker fuel management deals with the fuel bunkering issues faced by different ships, such as selection of bunkering ports and total bunkered amount at a port. A novel mathematical model is developed capturing the intricacies of the problem. A hybrid particle swarm optimization with a basic variable neighborhood search algorithm is proposed to solve the model and compared with the exact solutions obtained using Cplex and other popular algorithms for several problem instances. The proposed algorithm outperforms other popular algorithms in all the instances in terms of the solution quality and provides good quality solutions with an average cost deviation of 5.99% from the optimal solution.
AB - This paper studies a novel sustainable ship routing problem considering a time window concept and bunker fuel management. Ship routing involves the decisions corresponding to the deployment of vessels to multiple ports and time window concept helps to maintain the service level of the port. Reducing carbon emissions within the maritime transportation domain remains one of the most significant challenges as it addresses the sustainability aspect. Bunker fuel management deals with the fuel bunkering issues faced by different ships, such as selection of bunkering ports and total bunkered amount at a port. A novel mathematical model is developed capturing the intricacies of the problem. A hybrid particle swarm optimization with a basic variable neighborhood search algorithm is proposed to solve the model and compared with the exact solutions obtained using Cplex and other popular algorithms for several problem instances. The proposed algorithm outperforms other popular algorithms in all the instances in terms of the solution quality and provides good quality solutions with an average cost deviation of 5.99% from the optimal solution.
KW - Carbon dioxide
KW - Fuels
KW - Marine vehicles
KW - Mathematical model
KW - Microsoft Windows
KW - Routing
KW - Ship routing
KW - Transportation
KW - bunker fuel management
KW - mixed integer linear programming model
KW - variable neighborhood search algorithm
UR - http://www.scopus.com/inward/record.url?scp=85081117752&partnerID=8YFLogxK
U2 - 10.1109/TITS.2019.2900490
DO - 10.1109/TITS.2019.2900490
M3 - Article
AN - SCOPUS:85081117752
SN - 1524-9050
VL - 21
SP - 986
EP - 997
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
IS - 3
M1 - 8667890
ER -