IDEAS home Printed from https://ideas.repec.org/p/tiu/tiutis/aa045849-1e10-4f84-96ca-42e2632c7adb.html
   My bibliography  Save this paper

Initialization in semidefinite programming via a self-dual, skew-symmetric embedding

Author

Listed:
  • de Klerk, E.

    (Tilburg University, School of Economics and Management)

  • Roos, C.
  • Terlaky, T.

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
    • Handle: RePEc:tiu:tiutis:aa045849-1e10-4f84-96ca-42e2632c7adb
    as

    Download full text from publisher

    File URL: https://pure.uvt.nl/ws/portalfiles/portal/845072/initi.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sturm, J.F. & Zhang, S., 1995. "Symmetric primal-dual path following algorithms for semidefinite programming," Econometric Institute Research Papers EI 9554-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Yinyu Ye & Michael J. Todd & Shinji Mizuno, 1994. "An O(√nL)-Iteration Homogeneous and Self-Dual Linear Programming Algorithm," Mathematics of Operations Research, INFORMS, vol. 19(1), pages 53-67, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ivanov, I.D. & de Klerk, E., 2007. "Parallel Implementation of a Semidefinite Programming Solver based on CSDP in a distributed memory cluster," Other publications TiSEM 9b41ff5e-2808-4d12-a58c-0, Tilburg University, School of Economics and Management.
    2. Terlaky, Tamas, 2001. "An easy way to teach interior-point methods," European Journal of Operational Research, Elsevier, vol. 130(1), pages 1-19, April.
    3. Kirschner, Felix & de Klerk, Etienne, 2023. "A predictor-corrector algorithm for semidefinite programming that uses the factor width cone," Other publications TiSEM 957e76ec-7f75-4e6e-adc4-c, Tilburg University, School of Economics and Management.
    4. Helmberg, C., 2002. "Semidefinite programming," European Journal of Operational Research, Elsevier, vol. 137(3), pages 461-482, March.
    5. E. de Klerk & C. Roos & T. Terlaky, 1998. "Polynomial Primal-Dual Affine Scaling Algorithms in Semidefinite Programming," Journal of Combinatorial Optimization, Springer, vol. 2(1), pages 51-69, March.
    6. de Klerk, E. & Pasechnik, D.V., 2004. "Products of positive forms, linear matrix inequalities, and Hilbert 17th problem for ternary forms," Other publications TiSEM 90713b98-8cb2-4d0c-981c-8, Tilburg University, School of Economics and Management.
    7. Petra Renáta Rigó & Zsolt Darvay, 2018. "Infeasible interior-point method for symmetric optimization using a positive-asymptotic barrier," Computational Optimization and Applications, Springer, vol. 71(2), pages 483-508, November.
    8. Badenbroek, Riley & Dahl, Joachim, 2020. "An Algorithm for Nonsymmetric Conic Optimization Inspired by MOSEK," Other publications TiSEM bcf7ef05-e4e6-4ce8-b2e9-6, Tilburg University, School of Economics and Management.
    9. Halicka, Margareta, 2002. "Analyticity of the central path at the boundary point in semidefinite programming," European Journal of Operational Research, Elsevier, vol. 143(2), pages 311-324, December.
    10. Ivanov, I.D. & de Klerk, E., 2007. "Parallel Implementation of a Semidefinite Programming Solver based on CSDP in a distributed memory cluster," Discussion Paper 2007-20, Tilburg University, Center for Economic Research.
    11. de Klerk, Etienne & Pasechnik, Dmitrii V., 2004. "Products of positive forms, linear matrix inequalities, and Hilbert 17th problem for ternary forms," European Journal of Operational Research, Elsevier, vol. 157(1), pages 39-45, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Enzo Busseti, 2019. "Derivative of a Conic Problem with a Unique Solution," Papers 1903.05753, arXiv.org, revised Mar 2019.
    2. Luo, Z-Q. & Sturm, J.F. & Zhang, S., 1998. "Conic convex programming and self-dual embedding," Econometric Institute Research Papers EI 9815, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Arjan B. Berkelaar & Jos F. Sturm & Shuzhong Zhang, 1997. "Polynomial Primal-Dual Cone Affine Scaling for Semidefinite Programming," Tinbergen Institute Discussion Papers 97-025/4, Tinbergen Institute.
    4. Mehdi Karimi & Levent Tunçel, 2020. "Primal–Dual Interior-Point Methods for Domain-Driven Formulations," Mathematics of Operations Research, INFORMS, vol. 45(2), pages 591-621, May.
    5. F. A. Potra & R. Sheng, 1998. "Superlinear Convergence of Interior-Point Algorithms for Semidefinite Programming," Journal of Optimization Theory and Applications, Springer, vol. 99(1), pages 103-119, October.
    6. Freund, Robert Michael. & Mizuno, Shinji., 1996. "Interior point methods : current status and future directions," Working papers 3924-96., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    7. Sturm, J.F., 2001. "Avoiding Numerical Cancellation in the Interior Point Method for Solving Semidefinite Programs," Discussion Paper 2001-27, Tilburg University, Center for Economic Research.
    8. Brendan O’Donoghue & Eric Chu & Neal Parikh & Stephen Boyd, 2016. "Conic Optimization via Operator Splitting and Homogeneous Self-Dual Embedding," Journal of Optimization Theory and Applications, Springer, vol. 169(3), pages 1042-1068, June.
    9. Berkelaar, Arjan & Dert, Cees & Oldenkamp, Bart, 1999. "A primal-dual decompsition-based interior point approach to two-stage stochastic linear programming," Serie Research Memoranda 0026, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    10. Zohrizadeh, Fariba & Josz, Cedric & Jin, Ming & Madani, Ramtin & Lavaei, Javad & Sojoudi, Somayeh, 2020. "A survey on conic relaxations of optimal power flow problem," European Journal of Operational Research, Elsevier, vol. 287(2), pages 391-409.
    11. E. de Klerk & C. Roos & T. Terlaky, 1998. "Polynomial Primal-Dual Affine Scaling Algorithms in Semidefinite Programming," Journal of Combinatorial Optimization, Springer, vol. 2(1), pages 51-69, March.
    12. Badenbroek, Riley & Dahl, Joachim, 2020. "An Algorithm for Nonsymmetric Conic Optimization Inspired by MOSEK," Other publications TiSEM bcf7ef05-e4e6-4ce8-b2e9-6, Tilburg University, School of Economics and Management.
    13. Coralia Cartis & Yiming Yan, 2016. "Active-set prediction for interior point methods using controlled perturbations," Computational Optimization and Applications, Springer, vol. 63(3), pages 639-684, April.
    14. Thomas Schmelzer & Raphael Hauser & Erling Andersen & Joachim Dahl, 2013. "Regression techniques for Portfolio Optimisation using MOSEK," Papers 1310.3397, arXiv.org.
    15. Kuo-Ling Huang & Sanjay Mehrotra, 2017. "Solution of Monotone Complementarity and General Convex Programming Problems Using a Modified Potential Reduction Interior Point Method," INFORMS Journal on Computing, INFORMS, vol. 29(1), pages 36-53, February.
    16. Coralia Cartis & Yiming Yan, 2016. "Active-set prediction for interior point methods using controlled perturbations," Computational Optimization and Applications, Springer, vol. 63(3), pages 639-684, April.
    17. Michael O’Sullivan & Arthur F. Veinott, Jr., 2017. "Polynomial-Time Computation of Strong and n -Present-Value Optimal Policies in Markov Decision Chains," Mathematics of Operations Research, INFORMS, vol. 42(3), pages 577-598, August.
    18. Berkelaar, A.B. & Dert, C.L. & Oldenkamp, K.P.B. & Zhang, S., 1999. "A primal-dual decomposition based interior point approach to two-stage stochastic linear programming," Econometric Institute Research Papers EI 9918-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    19. Sturm, J.F., 2002. "Implementation of Interior Point Methods for Mixed Semidefinite and Second Order Cone Optimization Problems," Discussion Paper 2002-73, Tilburg University, Center for Economic Research.
    20. Zhang, S., 2002. "An interior-point and decomposition approach to multiple stage stochastic programming," Econometric Institute Research Papers EI 2002-35, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tiu:tiutis:aa045849-1e10-4f84-96ca-42e2632c7adb. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Richard Broekman (email available below). General contact details of provider: https://www.tilburguniversity.edu/about/schools/economics-and-management/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.