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Liquefied Natural Gas Logistics Management Through Optimal Road-Rail Intermodal Logistics Planning Considering Community Safety: A Case Study in Thailand

Author

Listed:
  • Porntip Junsang

    (King Mongkut's University of Technology Thonburi, Thailand)

  • Chorkaew Jaturanonda

    (King Mongkut's University of Technology Thonburi, Thailand)

  • Teeradej Wuttipornpun

    (King Mongkut's University of Technology North Bangkok, Thailand)

  • Mayurachat Watcharejyothin

    (PTT Public Company Limited, Thailand)

Abstract

The demand for natural gas (NG) in Thailand has been continuously increasing, but part of NG volume has not been distributed to customers locating far from the pipeline network. Therefore, NG is transported by trucks in liquid form called liquefied natural gas (LNG) to meet the demand. However, road transportation by truck causes many problems such as high transportation cost, low capacity, poor environmental conditions, and low safety. To solve these problems, the road-rail intermodal transportation is an option to distribute a large volume of LNG in long-haul transportation more efficiently. This research proposes an optimal planning for LNG logistics management in a case study where the problem is modeled as a mixed-integer nonlinear program to minimize the total logistics cost. The optimal solution includes the LNG distribution center locations, transportation mode(s), train loading service type, and truck type. Community safety using the LNG damage radius criterion is considered in the model as a constraint. The solutions resulting from three planning scenarios are compared and discussed.

Suggested Citation

  • Porntip Junsang & Chorkaew Jaturanonda & Teeradej Wuttipornpun & Mayurachat Watcharejyothin, 2023. "Liquefied Natural Gas Logistics Management Through Optimal Road-Rail Intermodal Logistics Planning Considering Community Safety: A Case Study in Thailand," International Journal of Knowledge and Systems Science (IJKSS), IGI Global, vol. 14(1), pages 1-25, January.
    • Handle: RePEc:igg:jkss00:v:14:y:2023:i:1:p:1-25
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