Time Reliability of the Maritime Transportation Network for China’s Crude Oil Imports

Shuang Wang*, Jing Lu, Liping Jiang

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

To evaluate the transportation time reliability of the maritime transportation network for China’s crude oil imports under node capacity variations resulting from extreme events, a framework incorporating bi-level programming and a Monte Carlo simulation is proposed in this paper. Under this framework, the imported crude oil volume from each source country is considered to be a decision variable, and may change in correspondence to node capacity variations. The evaluation results illustrate that when strait or canal nodes were subject to capacity variations, the network transportation time reliability was relatively low. Conversely, the transportation time reliability was relatively high when port nodes were under capacity variations. In addition, the Taiwan Strait, the Strait of Hormuz, and the Strait of Malacca were identified as vulnerable nodes according to the transportation time reliability results. These results can assist government decision-makers and tanker company strategic planners to better plan crude oil import and transportation strategies.
Original languageEnglish
Article number198
JournalSustainability
Volume12
Issue number1
Number of pages18
ISSN2071-1050
DOIs
Publication statusPublished - 2020

Keywords

  • Transportation time reliability
  • China’s crude oil imports
  • Maritime transportation network
  • Capacity variations
  • Bi-level programming
  • Monte Carlo simulation

Cite this

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title = "Time Reliability of the Maritime Transportation Network for China’s Crude Oil Imports",
abstract = "To evaluate the transportation time reliability of the maritime transportation network for China’s crude oil imports under node capacity variations resulting from extreme events, a framework incorporating bi-level programming and a Monte Carlo simulation is proposed in this paper. Under this framework, the imported crude oil volume from each source country is considered to be a decision variable, and may change in correspondence to node capacity variations. The evaluation results illustrate that when strait or canal nodes were subject to capacity variations, the network transportation time reliability was relatively low. Conversely, the transportation time reliability was relatively high when port nodes were under capacity variations. In addition, the Taiwan Strait, the Strait of Hormuz, and the Strait of Malacca were identified as vulnerable nodes according to the transportation time reliability results. These results can assist government decision-makers and tanker company strategic planners to better plan crude oil import and transportation strategies.",
keywords = "Transportation time reliability, China’s crude oil imports, Maritime transportation network, Capacity variations, Bi-level programming, Monte Carlo simulation, Transportation time reliability, China’s crude oil imports, Maritime transportation network, Capacity variations, Bi-level programming, Monte Carlo simulation",
author = "Shuang Wang and Jing Lu and Liping Jiang",
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publisher = "MDPI",
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Time Reliability of the Maritime Transportation Network for China’s Crude Oil Imports. / Wang, Shuang; Lu, Jing; Jiang, Liping.

In: Sustainability, Vol. 12, No. 1, 198, 2020.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Time Reliability of the Maritime Transportation Network for China’s Crude Oil Imports

AU - Wang, Shuang

AU - Lu, Jing

AU - Jiang, Liping

PY - 2020

Y1 - 2020

N2 - To evaluate the transportation time reliability of the maritime transportation network for China’s crude oil imports under node capacity variations resulting from extreme events, a framework incorporating bi-level programming and a Monte Carlo simulation is proposed in this paper. Under this framework, the imported crude oil volume from each source country is considered to be a decision variable, and may change in correspondence to node capacity variations. The evaluation results illustrate that when strait or canal nodes were subject to capacity variations, the network transportation time reliability was relatively low. Conversely, the transportation time reliability was relatively high when port nodes were under capacity variations. In addition, the Taiwan Strait, the Strait of Hormuz, and the Strait of Malacca were identified as vulnerable nodes according to the transportation time reliability results. These results can assist government decision-makers and tanker company strategic planners to better plan crude oil import and transportation strategies.

AB - To evaluate the transportation time reliability of the maritime transportation network for China’s crude oil imports under node capacity variations resulting from extreme events, a framework incorporating bi-level programming and a Monte Carlo simulation is proposed in this paper. Under this framework, the imported crude oil volume from each source country is considered to be a decision variable, and may change in correspondence to node capacity variations. The evaluation results illustrate that when strait or canal nodes were subject to capacity variations, the network transportation time reliability was relatively low. Conversely, the transportation time reliability was relatively high when port nodes were under capacity variations. In addition, the Taiwan Strait, the Strait of Hormuz, and the Strait of Malacca were identified as vulnerable nodes according to the transportation time reliability results. These results can assist government decision-makers and tanker company strategic planners to better plan crude oil import and transportation strategies.

KW - Transportation time reliability

KW - China’s crude oil imports

KW - Maritime transportation network

KW - Capacity variations

KW - Bi-level programming

KW - Monte Carlo simulation

KW - Transportation time reliability

KW - China’s crude oil imports

KW - Maritime transportation network

KW - Capacity variations

KW - Bi-level programming

KW - Monte Carlo simulation

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DO - 10.3390/su12010198

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VL - 12

JO - Sustainability

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