Planning a maritime supply chain for liquefied natural gas under uncertainty

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Planning a maritime supply chain for liquefied natural gas under uncertainty. / Eriksen, Ulrik; Kristiansen, Johan; Fagerholt, Kjetil; Pantuso, Giovanni.

I: Maritime Transport Research, Bind 3, 100061, 2022.

Publikation: Bidrag til tidsskriftTidsskriftartikelfagfællebedømt

Harvard

Eriksen, U, Kristiansen, J, Fagerholt, K & Pantuso, G 2022, 'Planning a maritime supply chain for liquefied natural gas under uncertainty', Maritime Transport Research, bind 3, 100061. https://doi.org/10.1016/j.martra.2022.100061

APA

Eriksen, U., Kristiansen, J., Fagerholt, K., & Pantuso, G. (2022). Planning a maritime supply chain for liquefied natural gas under uncertainty. Maritime Transport Research, 3, [100061]. https://doi.org/10.1016/j.martra.2022.100061

Vancouver

Eriksen U, Kristiansen J, Fagerholt K, Pantuso G. Planning a maritime supply chain for liquefied natural gas under uncertainty. Maritime Transport Research. 2022;3. 100061. https://doi.org/10.1016/j.martra.2022.100061

Author

Eriksen, Ulrik ; Kristiansen, Johan ; Fagerholt, Kjetil ; Pantuso, Giovanni. / Planning a maritime supply chain for liquefied natural gas under uncertainty. I: Maritime Transport Research. 2022 ; Bind 3.

Bibtex

@article{b0bd6e0b186f415490f3caabb7cad194,
title = "Planning a maritime supply chain for liquefied natural gas under uncertainty",
abstract = "This paper studies the design of a mid-scale maritime supply chain for distribution of liquefied natural gas (LNG) from overseas sourcing locations, via a storage located at the coast, before transporting the LNG on land to industrial customers. The case company has signed contracts with a number of initial customers and expect that there will be more customers and increased demand in the years to come. However, it is currently uncertain whether and when new contracts will be signed. To capture this uncertainty with regard to which and how many future customers there will be, which directly affects the demand, we propose a multi-stage stochastic programming model, which maximizes the expected profits of the supply chain. The model aims at aiding decisions concerning the import of LNG, investments in floating storage units and customer distribution systems, and it has been applied on a real case study for distributing LNG to customers in a Brazilian state. It is shown that explicitly considering uncertainty in the modeling of this problem is very important, with a Value of Stochastic Solution of 13.2%, and that there are significant economies of scale in this supply chain. Most importantly, the multi-stage stochastic programming model and the analysis presented in this paper provided valuable decision support and managerial insights for the case company in its process of setting up the LNG supply chain.",
keywords = "Liquefied natural gas, Maritime supply chain, Stochastic programming",
author = "Ulrik Eriksen and Johan Kristiansen and Kjetil Fagerholt and Giovanni Pantuso",
note = "Publisher Copyright: {\textcopyright} 2022 The Authors",
year = "2022",
doi = "10.1016/j.martra.2022.100061",
language = "English",
volume = "3",
journal = "Maritime Transport Research",
issn = "2666-822X",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Planning a maritime supply chain for liquefied natural gas under uncertainty

AU - Eriksen, Ulrik

AU - Kristiansen, Johan

AU - Fagerholt, Kjetil

AU - Pantuso, Giovanni

N1 - Publisher Copyright: © 2022 The Authors

PY - 2022

Y1 - 2022

N2 - This paper studies the design of a mid-scale maritime supply chain for distribution of liquefied natural gas (LNG) from overseas sourcing locations, via a storage located at the coast, before transporting the LNG on land to industrial customers. The case company has signed contracts with a number of initial customers and expect that there will be more customers and increased demand in the years to come. However, it is currently uncertain whether and when new contracts will be signed. To capture this uncertainty with regard to which and how many future customers there will be, which directly affects the demand, we propose a multi-stage stochastic programming model, which maximizes the expected profits of the supply chain. The model aims at aiding decisions concerning the import of LNG, investments in floating storage units and customer distribution systems, and it has been applied on a real case study for distributing LNG to customers in a Brazilian state. It is shown that explicitly considering uncertainty in the modeling of this problem is very important, with a Value of Stochastic Solution of 13.2%, and that there are significant economies of scale in this supply chain. Most importantly, the multi-stage stochastic programming model and the analysis presented in this paper provided valuable decision support and managerial insights for the case company in its process of setting up the LNG supply chain.

AB - This paper studies the design of a mid-scale maritime supply chain for distribution of liquefied natural gas (LNG) from overseas sourcing locations, via a storage located at the coast, before transporting the LNG on land to industrial customers. The case company has signed contracts with a number of initial customers and expect that there will be more customers and increased demand in the years to come. However, it is currently uncertain whether and when new contracts will be signed. To capture this uncertainty with regard to which and how many future customers there will be, which directly affects the demand, we propose a multi-stage stochastic programming model, which maximizes the expected profits of the supply chain. The model aims at aiding decisions concerning the import of LNG, investments in floating storage units and customer distribution systems, and it has been applied on a real case study for distributing LNG to customers in a Brazilian state. It is shown that explicitly considering uncertainty in the modeling of this problem is very important, with a Value of Stochastic Solution of 13.2%, and that there are significant economies of scale in this supply chain. Most importantly, the multi-stage stochastic programming model and the analysis presented in this paper provided valuable decision support and managerial insights for the case company in its process of setting up the LNG supply chain.

KW - Liquefied natural gas

KW - Maritime supply chain

KW - Stochastic programming

UR - http://www.scopus.com/inward/record.url?scp=85132048683&partnerID=8YFLogxK

U2 - 10.1016/j.martra.2022.100061

DO - 10.1016/j.martra.2022.100061

M3 - Journal article

AN - SCOPUS:85132048683

VL - 3

JO - Maritime Transport Research

JF - Maritime Transport Research

SN - 2666-822X

M1 - 100061

ER -

ID: 311863209