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Strong duality and minimal representations for cone optimization

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  • Levent Tunçel
  • Henry Wolkowicz

Abstract

The elegant theoretical results for strong duality and strict complementarity for linear programming, LP, lie behind the success of current algorithms. In addition, preprocessing is an essential step for efficiency in both simplex type and interior-point methods. However, the theory and preprocessing techniques can fail for cone programming over nonpolyhedral cones. We take a fresh look at known and new results for duality, optimality, constraint qualifications, CQ, and strict complementarity, for linear cone optimization problems in finite dimensions. One theme is the notion of minimal representation of the cone and the constraints. This provides a framework for preprocessing cone optimization problems in order to avoid both the theoretical and numerical difficulties that arise due to the (near) loss of the strong CQ, strict feasibility. We include results and examples on the surprising theoretical connection between duality gaps in the original primal-dual pair and lack of strict complementarity in their homogeneous counterpart. Our emphasis is on results that deal with Semidefinite Programming, SDP. Copyright Springer Science+Business Media, LLC 2012

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  • Levent Tunçel & Henry Wolkowicz, 2012. "Strong duality and minimal representations for cone optimization," Computational Optimization and Applications, Springer, vol. 53(2), pages 619-648, October.
  • Handle: RePEc:spr:coopap:v:53:y:2012:i:2:p:619-648
    DOI: 10.1007/s10589-012-9480-0
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    References listed on IDEAS

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    1. Kartik Krishnan & Tamás Terlaky, 2005. "Interior Point and Semidefinite Approaches in Combinatorial Optimization," Springer Books, in: David Avis & Alain Hertz & Odile Marcotte (ed.), Graph Theory and Combinatorial Optimization, chapter 0, pages 101-157, Springer.
    2. Helmberg, C., 2002. "Semidefinite programming," European Journal of Operational Research, Elsevier, vol. 137(3), pages 461-482, March.
    3. Maria Gonzalez-Lima & Hua Wei & Henry Wolkowicz, 2009. "A stable primal–dual approach for linear programming under nondegeneracy assumptions," Computational Optimization and Applications, Springer, vol. 44(2), pages 213-247, November.
    4. Csaba Mészáros & Jacek Gondzio, 2001. "Addendum to "Presolve Analysis of Linear Programs Prior to Applying an Interior Point Method"," INFORMS Journal on Computing, INFORMS, vol. 13(2), pages 169-170, May.
    5. Gábor Pataki, 2007. "On the Closedness of the Linear Image of a Closed Convex Cone," Mathematics of Operations Research, INFORMS, vol. 32(2), pages 395-412, May.
    6. Halická, M. & de Klerk, E. & Roos, C., 2002. "On the convergence of the central path in semidefinite optimization," Other publications TiSEM 9ca12b89-1208-46aa-8d70-4, Tilburg University, School of Economics and Management.
    7. Jacek Gondzio, 1997. "Presolve Analysis of Linear Programs Prior to Applying an Interior Point Method," INFORMS Journal on Computing, INFORMS, vol. 9(1), pages 73-91, February.
    8. Qing Zhao & Stefan E. Karisch & Franz Rendl & Henry Wolkowicz, 1998. "Semidefinite Programming Relaxations for the Quadratic Assignment Problem," Journal of Combinatorial Optimization, Springer, vol. 2(1), pages 71-109, March.
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    Cited by:

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