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Decomposition-based Inner- and Outer-Refinement Algorithms for Global Optimization

Author

Listed:
  • Ivo Nowak

    (Hamburg University of Applied Sciences)

  • Norman Breitfeld

    (Technische Universität Berlin)

  • Eligius M. T. Hendrix

    (Universidad de Málaga
    Wageningen University)

  • Grégoire Njacheun-Njanzoua

    (Hamburg University of Applied Sciences)

Abstract

Traditional deterministic global optimization methods are often based on a Branch-and-Bound (BB) search tree, which may grow rapidly, preventing the method to find a good solution. Motivated by decomposition-based inner approximation (column generation) methods for solving transport scheduling problems with over 100 million variables, we present a new deterministic decomposition-based successive approximation method for general modular and/or sparse MINLPs. The new method, called Decomposition-based Inner- and Outer-Refinement, is based on a block-separable reformulation of the model into sub-models. It generates inner- and outer-approximations using column generation, which are successively refined by solving many easier MINLP and MIP subproblems in parallel (using BB), instead of searching over one (global) BB search tree. We present preliminary numerical results with Decogo (Decomposition-based Global Optimizer), a new parallel decomposition MINLP solver implemented in Python and Pyomo.

Suggested Citation

  • Ivo Nowak & Norman Breitfeld & Eligius M. T. Hendrix & Grégoire Njacheun-Njanzoua, 2018. "Decomposition-based Inner- and Outer-Refinement Algorithms for Global Optimization," Journal of Global Optimization, Springer, vol. 72(2), pages 305-321, October.
    • Handle: RePEc:spr:jglopt:v:72:y:2018:i:2:d:10.1007_s10898-018-0633-2
    DOI: 10.1007/s10898-018-0633-2
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    References listed on IDEAS

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    1. Marco E. Lübbecke & Jacques Desrosiers, 2005. "Selected Topics in Column Generation," Operations Research, INFORMS, vol. 53(6), pages 1007-1023, December.
    2. 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.
    3. Ruth Misener & Christodoulos Floudas, 2014. "ANTIGONE: Algorithms for coNTinuous / Integer Global Optimization of Nonlinear Equations," Journal of Global Optimization, Springer, vol. 59(2), pages 503-526, July.
    4. Thorsten Koch & Ted Ralphs & Yuji Shinano, 2012. "Could we use a million cores to solve an integer program?," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 76(1), pages 67-93, August.
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    Cited by:

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    7. Pavlo Muts & Ivo Nowak & Eligius M. T. Hendrix, 2020. "The decomposition-based outer approximation algorithm for convex mixed-integer nonlinear programming," Journal of Global Optimization, Springer, vol. 77(1), pages 75-96, May.

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