A binary particle swarm optimization algorithm for ship routing and scheduling of liquefied natural gas transportation

Karbassi Yazdi, Amir, Kaviani, Mohamad Amin, Emrouznejad, Ali and Sahebi, Hadi (2019). A binary particle swarm optimization algorithm for ship routing and scheduling of liquefied natural gas transportation. Transportation Letters ,

Abstract

With the increasing global demands for energy, fuel supply management is a challenging task of today’s industries in order to decrease the cost of energy and diminish its adverse environmental impacts. To have a more environmentally friendly fuel supply network, Liquefied Natural Gas (LNG) is suggested as one of the best choices for manufacturers. As the consumption rate of LNG is increasing dramatically in the world, many companies try to carry this product all around the world by themselves or outsource it to third-party companies. However, the challenge is that the transportation of LNG requires specific vessels and there are many clauses in related LNG transportation contracts which may reduce the revenue of these companies, it seems essential to find the best option for them. The aim of this paper is to propose a meta-heuristic Binary Particle Swarm Optimization (BPSO) algorithm to come with an optimized solution for ship routing and scheduling of LNG transportation. The application demonstrates what sellers need to do to reduce their costs and increase their profits by considering or removing some obligations.

Publication DOI: https://doi.org/10.1080/19427867.2019.1581485
Divisions: Aston Business School > Operations & Information Management
Aston Business School
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis Group in Transportation Letters on 26 Feb 2019, available online at: http://www.tandfonline.com/10.1080/19427867.2019.1581485
Uncontrolled Keywords: Binary particle swarm optimization,liquefied natural gas,optimization,scheduling,ship routing,transportation,Transportation
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.tan ... 67.2019.1581485 (Publisher URL)
Published Date: 2019-02-26
Authors: Karbassi Yazdi, Amir
Kaviani, Mohamad Amin
Emrouznejad, Ali ( 0000-0001-8094-4244)
Sahebi, Hadi

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Version: Accepted Version

Access Restriction: Restricted to Repository staff only until 26 February 2020.


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