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Lookup NU author(s): Dr Arijit DeORCiD
This is the authors' accepted manuscript of an article that has been published in its final definitive form by IEEE, 2019.
For re-use rights please refer to the publisher's terms and conditions.
This research addresses the sustainability and safety related challenges associated with the complex, practical, and real-time maritime transportation problem, and proposes a multiobjective mathematical model integrating different shipping operations. A mixed integer nonlinear programming (MINLP) model is formulated considering different maritime operations, such as routing and scheduling of ships, time window concept considering port's high tidal scenario, discrete planning horizon, loading/unloading operation, carbon emission from the vessel, and ship's draft restriction for maintaining the vessel's safety at the port. The relationship between fuel consumption and vessel speed optimization is included in the model for the estimation of the total fuel consumed and carbon emission from each vessel. Time window concept considered in the problem aims to improve the service level of the port by imposing different penalty charges associated with the early arrival of the vessel before the starting of the time window and vessel failing to finish its operation within the allotted time window. Another practical aspect of the maritime transportation such as high tide scenario is included in the model to depict the vessel arrival and departure time at a port. Two novel algorithms Nondominated sorting genetic algorithm II (NSGA-II) and Multiobjective particle swarm optimization have been applied to solve the multiobjective mathematical model. The illustrative examples inspired from the real-life problems of an international shipping company are considered for application. The experimental results, comparative, and sensitivity analysis demonstrate the robustness of the proposed model.
Author(s): De A, Choudhary A, Tiwari MK
Publication type: Article
Publication status: Published
Journal: IEEE Transactions on Engineering Management
Year: 2019
Volume: 28
Issue: 1
Pages: 117-133
Print publication date: 01/01/2019
Online publication date: 04/12/2017
Acceptance date: 25/09/2017
Date deposited: 25/10/2018
ISSN (print): 0018-9391
ISSN (electronic): 1558-0040
Publisher: IEEE
URL: https://doi.org/10.1109/TEM.2017.2766443
DOI: 10.1109/TEM.2017.2766443
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