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Semidefinite programming

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  • Helmberg, C.

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  • Helmberg, C., 2002. "Semidefinite programming," European Journal of Operational Research, Elsevier, vol. 137(3), pages 461-482, March.
    • Handle: RePEc:eee:ejores:v:137:y:2002:i:3:p:461-482
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    References listed on IDEAS

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    1. Yu. E. Nesterov & M. J. Todd, 1997. "Self-Scaled Barriers and Interior-Point Methods for Convex Programming," Mathematics of Operations Research, INFORMS, vol. 22(1), pages 1-42, February.
    2. NESTEROV , Yurii & TODD , Michael, 1995. "Primal-Dual Interior-Point Methods for Self-Scaled Cones," LIDAM Discussion Papers CORE 1995044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. A. Ben-Tal & A. Nemirovski, 1998. "Robust Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 23(4), pages 769-805, November.
    4. de Klerk, E. & Roos, C. & Terlaky, T., 1997. "Initialization in semidefinite programming via a self-dual, skew-symmetric embedding," Other publications TiSEM aa045849-1e10-4f84-96ca-4, Tilburg University, School of Economics and Management.
    5. NESTEROV ., Yurii E. & TODD , Michael J, 1994. "Self-Scaled Cones and Interior-Point Methods in Nonlinear Programming," LIDAM Discussion Papers CORE 1994062, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. J. Frédéric Bonnans & Roberto Cominetti & Alexander Shapiro, 1998. "Sensitivity Analysis of Optimization Problems Under Second Order Regular Constraints," Mathematics of Operations Research, INFORMS, vol. 23(4), pages 806-831, November.
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    Cited by:

    1. Hanif Sherali & Evrim Dalkiran & Jitamitra Desai, 2012. "Enhancing RLT-based relaxations for polynomial programming problems via a new class of v-semidefinite cuts," Computational Optimization and Applications, Springer, vol. 52(2), pages 483-506, June.
    2. Liguo Jiao & Jae Hyoung Lee, 2018. "Approximate Optimality and Approximate Duality for Quasi Approximate Solutions in Robust Convex Semidefinite Programs," Journal of Optimization Theory and Applications, Springer, vol. 176(1), pages 74-93, January.
    3. Gicquel, C. & Lisser, A. & Minoux, M., 2014. "An evaluation of semidefinite programming based approaches for discrete lot-sizing problems," European Journal of Operational Research, Elsevier, vol. 237(2), pages 498-507.
    4. 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.
    5. F. Rendl, 2016. "Semidefinite relaxations for partitioning, assignment and ordering problems," Annals of Operations Research, Springer, vol. 240(1), pages 119-140, May.
    6. Yong Xia & Ying-Wei Han, 2014. "Partial Lagrangian relaxation for the unbalanced orthogonal Procrustes problem," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 79(2), pages 225-237, April.
    7. Xia, Yong & Sheu, Ruey-Lin & Sun, Xiaoling & Li, Duan, 2012. "Improved estimation of duality gap in binary quadratic programming using a weighted distance measure," European Journal of Operational Research, Elsevier, vol. 218(2), pages 351-357.
    8. J. Li & N. J. Huang, 2010. "Image Space Analysis for Vector Variational Inequalities with Matrix Inequality Constraints and Applications," Journal of Optimization Theory and Applications, Springer, vol. 145(3), pages 459-477, June.

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