A binary particle swarm optimization algorithm for ship routing and scheduling of liquefied natural gas transportation. Issue 4 (20th April 2020)

• Record Type: Journal Article
• Authors: Karbassi Yazdi, Amir; Kaviani, Mohamad Amin; Emrouznejad, Ali; Sahebi, Hadi
• Is Part Of: Transportation letters. Volume 12:Issue 4(2020)
• Page Start: 223
• Page End: 232
• Publication Date: 2020-04-20
• Subjects: Binary particle swarm optimization -- ship routing -- scheduling -- transportation -- liquefied natural gas -- optimization; Transportation -- Research -- Periodicals; Transportation -- Periodicals; Urban transportation -- Periodicals; 388.072
• DOI: 10.1080/19427867.2019.1581485
• Languages: English
• ISSNs: 1942-7867

Abstract

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.