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Liquefied natural gas inventory routing problem under uncertain weather conditions

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  • Cho, Jaeyoung
  • Lim, Gino J.
  • Kim, Seon Jin
  • Biobaku, Taofeek

Abstract

We study the liquefied natural gas (LNG) production-inventory control and vessel routing problem under disruptive weather conditions. If extreme weather is expected to strike an LNG plant, all planned LNG loading operations should be rescheduled to prevent expected safety accidents. We propose two mathematical optimization models to cope with the potential disruptions. The first model is formulated as a two-stage stochastic mixed integer program to maximize the overall expected revenue while minimizing the cost caused by the uncertain impact of weather disruptions. The second model is a decision maker's preference model that reflects a decision maker's evaluation of risk. This model enables a decision maker to have a ’what-if’ analysis by varying the level of preference for risks. The two proposed mathematical models can be reduced to a vehicle routing problem which is an NP-hard combinatorial optimization problem. Therefore, two computational techniques have developed to improve the optimization performance. First, a probing-based preprocessing technique is developed to reduce the solution space by eliminating obvious infeasible or non-optimal solutions. Second, an optional logical inequality is developed to generate an upper bound for the optimal solution only if an LNG carrier visits one or two customers in a single tour. Computational results indicate our proposed models and computational techniques are well suited to solve the problem within a reasonable time.

Suggested Citation

  • Cho, Jaeyoung & Lim, Gino J. & Kim, Seon Jin & Biobaku, Taofeek, 2018. "Liquefied natural gas inventory routing problem under uncertain weather conditions," International Journal of Production Economics, Elsevier, vol. 204(C), pages 18-29.
  • Handle: RePEc:eee:proeco:v:204:y:2018:i:c:p:18-29
    DOI: 10.1016/j.ijpe.2018.07.014
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    References listed on IDEAS

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    3. Shivam Gupta & Sachin Modgil & Ajay Kumar & Uthayasankar Sivarajah & Zahir Irani, 2022. "Artificial intelligence and cloud-based Collaborative Platforms for Managing Disaster, extreme weather and emergency operations," Post-Print hal-04325638, HAL.
    4. Gupta, Shivam & Modgil, Sachin & Kumar, Ajay & Sivarajah, Uthayasankar & Irani, Zahir, 2022. "Artificial intelligence and cloud-based Collaborative Platforms for Managing Disaster, extreme weather and emergency operations," International Journal of Production Economics, Elsevier, vol. 254(C).
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    6. Saura, Jose Ramon & Ribeiro-Navarrete, Samuel & Palacios-Marqués, Daniel & Mardani, Abbas, 2023. "Impact of extreme weather in production economics: Extracting evidence from user-generated content," International Journal of Production Economics, Elsevier, vol. 260(C).
    7. Dara, Satyadileep & Abdulqader, Haytham & Al Wahedi, Yasser & Berrouk, Abdallah S., 2020. "Countrywide optimization of natural gas supply chain: From wells to consumers," Energy, Elsevier, vol. 196(C).
    8. Ghiami, Yousef & Demir, Emrah & Van Woensel, Tom & Christiansen, Marielle & Laporte, Gilbert, 2019. "A deteriorating inventory routing problem for an inland liquefied natural gas distribution network," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 45-67.
    9. Tian, Xin & Cao, Shasha & Song, Yan, 2021. "The impact of weather on consumer behavior and retail performance: Evidence from a convenience store chain in China," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    10. Rigot-Müller, Patrick & Cheaitou, Ali & Etienne, Laurent & Faury, Olivier & Fedi, Laurent, 2022. "The role of polarseaworthiness in shipping planning for infrastructure projects in the Arctic: The case of Yamal LNG plant," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 330-353.
    11. Liang, Chen & Zhu, Minghao & Lee, Peter K.C. & Cheng, T.C.E. & Yeung, Andy C.L., 2024. "Combating extreme weather through operations management: Evidence from a natural experiment in China," International Journal of Production Economics, Elsevier, vol. 267(C).
    12. Liang, Chao & Xia, Zhenglan & Lai, Xiaodong & Wang, Lu, 2022. "Natural gas volatility prediction: Fresh evidence from extreme weather and extended GARCH-MIDAS-ES model," Energy Economics, Elsevier, vol. 116(C).
    13. Cao, Kaiying & Guo, Qiang & Xu, Yuqiu, 2023. "Information sharing and carbon reduction strategies with extreme weather in the platform economy," International Journal of Production Economics, Elsevier, vol. 255(C).
    14. Saleh Aseel & Hussein Al-Yafei & Murat Kucukvar & Nuri C. Onat, 2021. "Life Cycle Air Emissions and Social Human Health Impact Assessment of Liquified Natural Gas Maritime Transport," Energies, MDPI, vol. 14(19), pages 1-19, September.

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