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Mixed-integer linear optimization for optimal lift-gas allocation with well-separator routing

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  • Codas, Andrés
  • Camponogara, Eduardo

Abstract

The lift-gas allocation problem with well-separator routing constraints is a mixed-integer nonlinear program of considerable complexity. To this end, a mixed-integer linear formulation (compact) is obtained by piecewise-linearizing the nonlinear curves, using binary variables to express the linearization and routing decisions. A new formulation (integrated) combining the decisions on linearization and routing is developed by using a single binary variable. The structures of both formulations are explored to generate lifted cover cuts. Numerical tests show that the solution of the integrated formulation using cutting-plane generation is faster in spite of having more variables than the compact formulation.

Suggested Citation

  • Codas, Andrés & Camponogara, Eduardo, 2012. "Mixed-integer linear optimization for optimal lift-gas allocation with well-separator routing," European Journal of Operational Research, Elsevier, vol. 217(1), pages 222-231.
    • Handle: RePEc:eee:ejores:v:217:y:2012:i:1:p:222-231
    DOI: 10.1016/j.ejor.2011.08.027
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    References listed on IDEAS

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    1. Camponogara, Eduardo & Nakashima, Paulo H.R., 2006. "Solving a gas-lift optimization problem by dynamic programming," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1220-1246, October.
    2. Kaparis, Konstantinos & Letchford, Adam N., 2008. "Local and global lifted cover inequalities for the 0-1 multidimensional knapsack problem," European Journal of Operational Research, Elsevier, vol. 186(1), pages 91-103, April.
    3. R. Misener & C. A. Floudas, 2010. "Piecewise-Linear Approximations of Multidimensional Functions," Journal of Optimization Theory and Applications, Springer, vol. 145(1), pages 120-147, April.
    4. Juan Pablo Vielma & Shabbir Ahmed & George Nemhauser, 2010. "Mixed-Integer Models for Nonseparable Piecewise-Linear Optimization: Unifying Framework and Extensions," Operations Research, INFORMS, vol. 58(2), pages 303-315, April.
    5. Harlan Crowder & Ellis L. Johnson & Manfred Padberg, 1983. "Solving Large-Scale Zero-One Linear Programming Problems," Operations Research, INFORMS, vol. 31(5), pages 803-834, October.
    6. VANDERBECK, François & WOLSEY, Laurence A., 2010. "Reformulation and decomposition of integer programs," LIDAM Reprints CORE 2188, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    Cited by:

    1. Silva, Thiago Lima & Camponogara, Eduardo, 2014. "A computational analysis of multidimensional piecewise-linear models with applications to oil production optimization," European Journal of Operational Research, Elsevier, vol. 232(3), pages 630-642.
    2. I. Gimenez-Palacios & M. T. Alonso & R. Alvarez-Valdes & F. Parreño, 2021. "Logistic constraints in container loading problems: the impact of complete shipment conditions," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 177-203, April.
    3. Eduardo Rauh Müller & Eduardo Camponogara & Laio Oriel Seman & Eduardo Otte Hülse & Bruno Ferreira Vieira & Luis Kin Miyatake & Alex Furtado Teixeira, 2022. "Short-term steady-state production optimization of offshore oil platforms: wells with dual completion (gas-lift and ESP) and flow assurance," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 152-180, April.
    4. Camponogara, Eduardo & Oliveira, Mateus Dubiela & Aguiar, Marco Aurélio Schmitz de, 2015. "Scheduling pumpoff operations in onshore oilfields under electric-power constraints," European Journal of Operational Research, Elsevier, vol. 247(3), pages 945-956.

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