Publication:
Bunkering policies for a fuel bunker management problem for liner shipping networks

dc.contributor.coauthorDe, Arijit
dc.contributor.coauthorChoudhary, Alok
dc.contributor.coauthorTiwari, Manoj K.
dc.contributor.departmentDepartment of Industrial Engineering
dc.contributor.kuauthorTürkay, Metin
dc.contributor.kuprofileFaculty Member
dc.contributor.otherDepartment of Industrial Engineering
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.yokid24956
dc.date.accessioned2024-11-10T00:09:21Z
dc.date.issued2021
dc.description.abstractThis paper investigates the problem of bunker fuel management for liner shipping networks under different fuel pricing scenarios and taking into consideration different fuel bunkering policies. The fuel consumption of a vessel on a sailing leg may fluctuate as the real vessel speed deviates from the planned vessel speed. Furthermore, fluctuation of fuel prices at various ports increases the complexity of bunkering decisions related to the selection of the bunkering ports and the estimation of bunkered fuel cost. We have developed a mixed integer non-linear programming model to minimize the total expected cost consisting of inventory cost related to container transportation, operating cost associated with ship hiring, as well as bunkering cost and fuel consumption cost at the port. The novelty of our research lies in its consideration of stochastic fuel consumption for different sailing legs, stochastic fuel prices at each port and different fuel bunkering policies to determine optimal bunker fuel management strategies for the selection of bunkering ports and for the estimation of the amount of bunkered fuel required. We have proposed a novel approximate algorithm based on mathematical formulation and the fuel bunkering policies to calculate the total expected cost; the fuel inventory while arriving at and departing from the port; the number of vessels hired for weekly service; the arrival and departure time of the ship; and the amount of fuel bunkered at a port. We have performed extensive computational experiments on the practical routes to demonstrate the applicability, efficacy and robustness of the proposed novel methodology.
dc.description.indexedbyWoS
dc.description.indexedbyScopus
dc.description.issue3
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsorshipEuropean Union Europe Aid [R/141842] We thank both the Editor and the reviewers for their constructive comments and contributions to enhance the quality, clarity and presentation of our research. This research has been made available through the European Union Europe Aid-funded Project "EU-India Research & Innovation Partnership for Efficient and Sustainable Freight Transportation (REINVEST)," Contract Number: R/141842. The contents of this publication are the sole responsibility of the authors of this paper and can in no way be taken to reflect the views of the European Union.
dc.description.volume289
dc.identifier.doi10.1016/j.ejor.2019.07.044
dc.identifier.eissn1872-6860
dc.identifier.issn0377-2217
dc.identifier.quartileQ1
dc.identifier.scopus2-s2.0-85070519119
dc.identifier.urihttp://dx.doi.org/10.1016/j.ejor.2019.07.044
dc.identifier.urihttps://hdl.handle.net/20.500.14288/17114
dc.identifier.wos596436100010
dc.keywordsHeuristics
dc.keywordsLiner shipping
dc.keywordsBunker fuel management
dc.keywordsBunkering policies
dc.keywordsApproximate algorithm speed optimization
dc.keywordsAlgorithm
dc.keywordsTime
dc.keywordsDesign
dc.keywordsShips
dc.keywordsPrice
dc.keywordsModel
dc.languageEnglish
dc.publisherElsevier
dc.sourceEuropean Journal of Operational Research
dc.subjectManagement
dc.subjectOperations research
dc.subjectManagement science
dc.titleBunkering policies for a fuel bunker management problem for liner shipping networks
dc.typeConference proceeding
dspace.entity.typePublication
local.contributor.authorid0000-0003-4769-6714
local.contributor.kuauthorTürkay, Metin
relation.isOrgUnitOfPublicationd6d00f52-d22d-4653-99e7-863efcd47b4a
relation.isOrgUnitOfPublication.latestForDiscoveryd6d00f52-d22d-4653-99e7-863efcd47b4a

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