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

Amir Karbassi Yazdi, Mohamad Amin Kaviani*, Ali Emrouznejad, Hadi Sahebi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)223-232
JournalTransportation Letters
Issue number4
Publication statusPublished - 26 Feb 2019

Bibliographical note

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


  • Binary particle swarm optimization
  • liquefied natural gas
  • optimization
  • scheduling
  • ship routing
  • transportation


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