Paper Info
Title
Hybridizing Basic Variable Neighborhood Search With Particle Swarm Optimization for Solving Sustainable Ship Routing and Bunker Management Problem
Abstract
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.
Year
DOI
Venue
2020
10.1109/TITS.2019.2900490
IEEE Transactions on Intelligent Transportation Systems
Keywords
DocType
Volume
Fuels,Marine vehicles,Routing,Carbon dioxide,Transportation,Mathematical model,Microsoft Windows
Journal
21
Issue
ISSN
Citations 
3
1524-9050
2
PageRank 
References 
Authors
0.36
0
3
Name
Order
Citations
PageRank
Arijit De1463.69
Wang, J.2606.72
M. K. Tiwari31240115.22