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LaGO: a (heuristic) Branch and Cut algorithm for nonconvex MINLPs

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  • Ivo Nowak
  • Stefan Vigerske

Abstract

We present a Branch and Cut algorithm of the software package LaGO to solve nonconvex mixed-integer nonlinear programs (MINLPs). A linear outer approximation is constructed from a convex relaxation of the problem. Since we do not require an algebraic representation of the problem, reformulation techniques for the construction of the convex relaxation cannot be applied, and we are restricted to sampling techniques in case of nonquadratic nonconvex functions. The linear relaxation is further improved by mixed-integer-rounding cuts. Also box reduction techniques are applied to improve efficiency. Numerical results on medium size test problems are presented to show the efficiency of the method. Copyright Springer-Verlag 2008

Suggested Citation

  • Ivo Nowak & Stefan Vigerske, 2008. "LaGO: a (heuristic) Branch and Cut algorithm for nonconvex MINLPs," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 16(2), pages 127-138, June.
    • Handle: RePEc:spr:cejnor:v:16:y:2008:i:2:p:127-138
    DOI: 10.1007/s10100-007-0051-x
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    References listed on IDEAS

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    1. MARCHAND, Hugues & WOLSEY, Laurence A., 2001. "Aggregation and mixed integer rounding to solve mips," LIDAM Reprints CORE 1513, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Hugues Marchand & Laurence A. Wolsey, 2001. "Aggregation and Mixed Integer Rounding to Solve MIPs," Operations Research, INFORMS, vol. 49(3), pages 363-371, June.
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    Cited by:

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    3. Pia Domschke & Bjorn Geißler & Oliver Kolb & Jens Lang & Alexander Martin & Antonio Morsi, 2011. "Combination of Nonlinear and Linear Optimization of Transient Gas Networks," INFORMS Journal on Computing, INFORMS, vol. 23(4), pages 605-617, November.
    4. Victor Reyes & Ignacio Araya, 2023. "Non-Convex Optimization: Using Preconditioning Matrices for Optimally Improving Variable Bounds in Linear Relaxations," Mathematics, MDPI, vol. 11(16), pages 1-19, August.
    5. Zhou Wei & M. Ali, 2015. "Convex mixed integer nonlinear programming problems and an outer approximation algorithm," Journal of Global Optimization, Springer, vol. 63(2), pages 213-227, October.

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