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Tighter MIP formulations for the discretised unit commitment problem with min-stop ramping constraints

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  • Nicolas Dupin

    (Univ. Lille, UMR 9189, CRIStAL, Centre de Recherche en Informatique Signal et Automatique de Lille)

Abstract

This paper elaborates compact MIP formulations for a discrete unit commitment problem with minimum stop and ramping constraints. The variables can be defined in two different ways. Both MIP formulations are tightened with clique cuts and local constraints. The projection of constraints from one variable structure to the other allows to compare and tighten the MIP formulations. This leads to several equivalent formulations in terms of polyhedral descriptions and thus in LP relaxations. We analyse how MIP resolutions differ in the efficiency of the cuts, branching and primal heuristics. The resulting MIP implementation allows to tackle real size instances for an industrial application.

Suggested Citation

  • Nicolas Dupin, 2017. "Tighter MIP formulations for the discretised unit commitment problem with min-stop ramping constraints," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 5(1), pages 149-176, March.
    • Handle: RePEc:spr:eurjco:v:5:y:2017:i:1:d:10.1007_s13675-016-0078-7
    DOI: 10.1007/s13675-016-0078-7
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    References listed on IDEAS

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    1. Samer Takriti & Benedikt Krasenbrink & Lilian S.-Y. Wu, 2000. "Incorporating Fuel Constraints and Electricity Spot Prices into the Stochastic Unit Commitment Problem," Operations Research, INFORMS, vol. 48(2), pages 268-280, April.
    2. Zonghao Gu & George L. Nemhauser & Martin W. P. Savelsbergh, 1998. "Lifted Cover Inequalities for 0-1 Integer Programs: Computation," INFORMS Journal on Computing, INFORMS, vol. 10(4), pages 427-437, November.
    3. Atamturk, Alper & Nemhauser, George L. & Savelsbergh, Martin W. P., 2000. "Conflict graphs in solving integer programming problems," European Journal of Operational Research, Elsevier, vol. 121(1), pages 40-55, February.
    4. M. W. P. Savelsbergh, 1994. "Preprocessing and Probing Techniques for Mixed Integer Programming Problems," INFORMS Journal on Computing, INFORMS, vol. 6(4), pages 445-454, November.
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    Cited by:

    1. Nicolas Dupin & El-Ghazali Talbi, 2021. "Matheuristics to optimize refueling and maintenance planning of nuclear power plants," Journal of Heuristics, Springer, vol. 27(1), pages 63-105, April.

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