Skip to main content

Central Path Curvature and Iteration-Complexity for Redundant Klee—Minty Cubes

  • Chapter
  • First Online:

Part of the book series: Advances in Mechanics and Mathematics ((AMMA,volume 17))

Summary

We consider a family of linear optimization problems over the n-dimensional Klee—Minty cube and show that the central path may visit all of its vertices in the same order as simplex methods do. This is achieved by carefully adding an exponential number of redundant constraints that forces the central path to take at least 2n–2 sharp turns. This fact suggests that any feasible path-following interior-point method will take at least O(2n) iterations to solve this problem, whereas in practice typically only a few iterations (e.g., 50) suffices to obtain a high-quality solution. Thus, the construction potentially exhibits the worst-case iteration-complexity known to date which almost matches the theoretical iteration-complexity bound for this type of methods. In addition, this construction gives a counterexample to a conjecture that the total central path curvature is O(n).

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. J-P. Dedieu, G. Malajovich, and M. Shub. On the curvature of the central path of linear programming theory. Foundations of Computational Mathematics, 5:145—171, 2005.

    Article  MathSciNet  MATH  Google Scholar 

  2. 1 J-P. Dedieu and M. Shub. Newton flow and interior point methods in linear programming. International Journal of Bifurcation and Chaos, 15:827—839, 2005.

    Article  MathSciNet  MATH  Google Scholar 

  3. A. Deza, T. Terlaky, and Y. Zinchenko.Polytopes and arrangements: Diameter and curvature. Operations Research Letters, 36-2:215—222, 2008.

    Article  MathSciNet  Google Scholar 

  4. A. Deza, E. Nematollahi, R. Peyghami, and T. Terlaky. The central path visits all the vertices of the Klee—Minty cube. Optimization Methods and Software, 21-5:851—865, 2006.

    Article  MathSciNet  Google Scholar 

  5. A. Deza, E. Nematollahi, and T. Terlaky. How good are interior point methods? Klee—Minty cubes tighten iteration-complexity bounds. Mathematical Programming, 113-1:1—14, 2008.

    Article  MathSciNet  Google Scholar 

  6. J. Gondzio. Presolve analysis of linear programs prior to applying an interior point method. INFORMS Journal on Computing, 9-1:73—91, 1997.

    Article  MathSciNet  Google Scholar 

  7. I. Maros. Computational Techniques of the Simplex Method. Kluwer Academic, Boston, MA.

    Google Scholar 

  8. N. Megiddo and M. Shub. Boundary behavior of interior point algorithms in linear programming. Mathematics of Operations Research, 14-1:97—146, 1989.

    Article  MathSciNet  Google Scholar 

  9. R. Monteiro and T. Tsuchiya. A strong bound on the integral of the central path curvature and its relationship with the iteration complexity of primal-dual path-following LP algorithms. Optimization Online, September 2005.

    Google Scholar 

  10. Yu. Nesterov and M. Todd. On the Riemannian geometry defined by self-concordant barriers and interior-point methods. Foundations of Computational Mathematics, 2:333—361, 2002.

    Article  MathSciNet  MATH  Google Scholar 

  11. C. Roos, T. Terlaky, and J-Ph. Vial. Theory and Algorithms for Linear Optimization: An Interior Point Approach. Springer, New York, second edition, 2006.

    Google Scholar 

  12. G. Sonnevend, J. Stoer, and G. Zhao. On the complexity of following the central path of linear programs by linear extrapolation. II. Mathematical Programming, 52:527—553, 1991.

    Article  MathSciNet  MATH  Google Scholar 

  13. M. Todd and Y. Ye. A lower bound on the number of iterations of long-step and polynomial interior-point linear programming algorithms. Annals of Operations Research, 62:233—252, 1996.

    Article  MathSciNet  MATH  Google Scholar 

  14. S. Vavasis and Y. Ye. A primal-dual interior-point method whose running time depends only on the constraint matrix. Mathematical Programming, 74:79—120, 1996.

    MathSciNet  MATH  Google Scholar 

  15. G. Zhao and J. Stoer. Estimating the complexity of a class of path-following methods for solving linear programs by curvature integrals. Applied Mathematics and Optimization, 27:85—103, 1993.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yuriy Zinchenko .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

Deza, A., Terlaky, T., Zinchenko, Y. (2009). Central Path Curvature and Iteration-Complexity for Redundant Klee—Minty Cubes. In: Gao, D., Sherali, H. (eds) Advances in Applied Mathematics and Global Optimization. Advances in Mechanics and Mathematics, vol 17. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-75714-8_7

Download citation

Publish with us

Policies and ethics