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A Mixed-Integer Programming Model for Gas Purchase and Transportation

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  • Luis Contesse
  • Juan Ferrer
  • Sergio Maturana

Abstract

The natural gas supply chain involves three main agents: producers, transportation companies, and local distribution companies (LDCs). We present a MIP model that is the basis for a decision support system developed for a Chilean LDC. This model takes into account many of the complexities of the purchasing and transportation contracts to help optimize daily purchase and transportation decisions in the absence of local storage facilities. The model was solved to optimality within a reasonable time. We show how the model handles several contractual issues and give some insights for the case when demand scenarios are used to deal with uncertainty. Copyright Springer Science + Business Media, Inc. 2005

Suggested Citation

  • Luis Contesse & Juan Ferrer & Sergio Maturana, 2005. "A Mixed-Integer Programming Model for Gas Purchase and Transportation," Annals of Operations Research, Springer, vol. 139(1), pages 39-63, October.
    • Handle: RePEc:spr:annopr:v:139:y:2005:i:1:p:39-63:10.1007/s10479-005-3443-0
    DOI: 10.1007/s10479-005-3443-0
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    References listed on IDEAS

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    Cited by:

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    4. Liang, Yingzong & Hui, Chi Wai, 2018. "Convexification for natural gas transmission networks optimization," Energy, Elsevier, vol. 158(C), pages 1001-1016.
    5. Zhao, Xu & Wang, Jiawei & Lei, Shan, 2023. "Does regional natural gas supply produce a shortfall under transition from coal to gas? Case study in Jing-Jin-Ji Region," Energy Policy, Elsevier, vol. 174(C).
    6. Hamedi, Maryam & Zanjirani Farahani, Reza & Husseini, Mohammad Moattar & Esmaeilian, Gholam Reza, 2009. "A distribution planning model for natural gas supply chain: A case study," Energy Policy, Elsevier, vol. 37(3), pages 799-812, March.
    7. Psarras, John, 2016. "Multicriteria decision support to evaluate potential long-term natural gas supply alternatives: The case of GreeceAuthor-Name: Androulaki, Stella," European Journal of Operational Research, Elsevier, vol. 253(3), pages 791-810.
    8. Sergei Schreider & Jonathan Plummer & Daniel McInnes & Boris Miller, 2015. "Sensitivity analysis of gas supply optimization models," Annals of Operations Research, Springer, vol. 226(1), pages 565-588, March.
    9. Zarei, Javad & Amin-Naseri, Mohammad Reza, 2019. "An integrated optimization model for natural gas supply chain," Energy, Elsevier, vol. 185(C), pages 1114-1130.
    10. Ozelkan, Ertunga C. & D'Ambrosio, Alfred & Teng, S. Gary, 2008. "Optimizing liquefied natural gas terminal design for effective supply-chain operations," International Journal of Production Economics, Elsevier, vol. 111(2), pages 529-542, February.
    11. Ríos-Mercado, Roger Z. & Borraz-Sánchez, Conrado, 2015. "Optimization problems in natural gas transportation systems: A state-of-the-art review," Applied Energy, Elsevier, vol. 147(C), pages 536-555.
    12. Bohle, Carlos & Maturana, Sergio & Vera, Jorge, 2010. "A robust optimization approach to wine grape harvesting scheduling," European Journal of Operational Research, Elsevier, vol. 200(1), pages 245-252, January.

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