Optimal planning of liquefied natural gas deliveries

The authors investigate the problem of designing an optimal annual delivery plan for Liquefied Natural Gas (LNG). This problem requires determining the long-term cargo delivery dates and the assignment of vessels to the cargoes while accommodating several constraints, including berth availability, liquefaction terminal inventory, planned maintenance, and bunkering requirements. The authors describe a novel mixed-integer programming formulation that captures important industry requirements and constraints with the objective of minimizing the vessel fleet size. A peculiar property of the proposed formulation is that it includes a polynomial number of variables and constraints and is, in the authors' experience, computationally tractable for large problem instances using a commercial solver. Extensive computational runs demonstrate the efficacy of the proposed model for real instances provided by a major energy company that involve up to 118 cargoes and a 373-day planning horizon.

• Record URL:
  https://doi.org/10.1016/j.trc.2016.05.017
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0968090X16300547
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Al-Haidous, Sara
  • Msakni, Mohamed Kais
  • Haouari, Mohamed
• Publication Date: 2016-8

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 79-90
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 69
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Delivery service; Liquefied natural gas; Merchant fleet operation; Mixed integer programming; Optimization; Supply chain management; Water transportation
• Subject Areas: Energy; Freight Transportation; Marine Transportation; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01608737
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 22 2016 4:24PM