Skip to main content

New Complexity Analysis of Primal-Dual Newton Methods for P *(κ) Linear Complementarity Problems

  • Chapter
Book cover High Performance Optimization

Part of the book series: Applied Optimization ((APOP,volume 33))

Abstract

In this paper, we consider a primal-dual Newton method for linear complementarity problems (LCP) with P *(κ)-matrix. By using some new analysis tools, we prove polynomial complexity of the large update method without using a barrier or potential function. Our analysis is based on an appropriate proximity measure only. This proximity measure has not been used in the analysis of a large update method for LCP before. Our new analysis provides a unified way to analyze both large update and small update methods. The polynomial complexity of the method of finding a maximally complementarity solution is discussed as well.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Cottle, R.W., J.S. Pang and V. Venkateswaran. Sufficient matrices and the linear complementarity problem. Linear Algebra and Its Applications, 114/115:231–249, 1989.

    Article  MathSciNet  Google Scholar 

  2. Cottle, R.W., J.S. Pang and R.E. Stone. The Linear Complementarity Problem. Academic Press, Boston, 1992.

    MATH  Google Scholar 

  3. Harker, P.T., and J.S. Pang. Finite dimensional variational inequality and nonlinear complementarity problems: A survey of theory, algorithms and applications. Mathematical Programming 48:1990, 161–220.

    Article  MathSciNet  MATH  Google Scholar 

  4. Illés, T., J.M. Peng, C. Roos and T. Terlaky. A strongly polynomial rounding procedure yielding a maximally complementarity solution for P*(κ) linear complementarity problems. To appear in SIAM Journal on Optimization.

    Google Scholar 

  5. Jansen, B., C. Roos, T. Terlaky and J.-Ph. Vial. Primal-dual algorithms for linear programming based on the logarithmic barrier method. Journal of Optimization Theory and Applications, 83:1–26, 1994.

    Article  MathSciNet  MATH  Google Scholar 

  6. Ji, J., F. Potra and S. Huang. A predictor-corrector method for linear complementarity problems with polynomial complexity and superlinear convergence. Journal of Optimization Theory and Applications, 84:187–199, 1995.

    Article  MathSciNet  Google Scholar 

  7. Kojima, M., S. Mizuno and A. Yoshise. A polynomial-time algorithm for a class of linear complementarity problems. Mathematical Programming, 44:1–26, 1989.

    Article  MathSciNet  MATH  Google Scholar 

  8. Kojima, M., S. Mizuno and A. Yoshise. An O(Math) iteration potential reduction algorithm for linear complementarity problems. Mathematical Programming, 50:331–342, 1991.

    Article  MathSciNet  MATH  Google Scholar 

  9. Kojima, M., N. Megiddo, T. Noma and A. Yoshise. A unified approach to interior point algorithms for linear complementarity problems, volume 538 of Lecture Notes in Computer Science. , Springer Verlag, Berlin Germany, 1991.

    Google Scholar 

  10. Mangasarian, O.L., and T.-H. Shiau. Lipschitz continuity of solutions of linear inequalities, programs and complementarity problems. SIAM J. Control and Optimization, 3(25), 583–595, 1987.

    Article  MathSciNet  Google Scholar 

  11. Mizuno, S., and A. Nagasawa. A primal-dual affine scaling potential reduction algorithm for linear programming. Mathematical Programming, 62:119–131, 1993.

    Article  MathSciNet  MATH  Google Scholar 

  12. Peng, J., C. Roos and T. Terlaky. New complexity analysis of the primal-dual Newton method for linear optimization. To appear in Annals of Operations Research.

    Google Scholar 

  13. Roos, C., T. Terlaky and J.-Ph. Vial. Theory and Algorithms for Linear Optimization: An Interior Point Approach. John Wiley & Sons., 1997.

    MATH  Google Scholar 

  14. Väliaho, H. Vmatrices are just sufficient. Linear Algebra and Its Applications, 233:109–129, 1996.

    Article  MathSciNet  MATH  Google Scholar 

  15. Ye, Y., and K. Anstreicher. On quadratic and O(Math) convergence of a predictor-corrector algorithm for LCP. Mathematical Programming, 62:537–552, 1993.

    Article  MathSciNet  MATH  Google Scholar 

  16. Ye, Y., M.J. Todd and S. Mizuno. An O(Math)-iteration homogeneous and self-dual linear programming algorithm. Mathematics of Operations Research, 59:53–67, 1994.

    Article  MathSciNet  Google Scholar 

  17. Yoshise, A. Complementarity Problems. In: T. Terlaky, ed., Interior Point Methods of Mathematical Programming, 297–367, Kluwer Academic Publishers, Dordrecht, 1996.

    Chapter  Google Scholar 

  18. Zhao, G.Y. Interior point algorithms for linear complementarity problems bcised on large neighborhoods of the central path. SIAM J. on Optimization, 8:397–413, 1998.

    Article  MATH  Google Scholar 

Download references

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Peng, J., Roos, C., Terlaky, T. (2000). New Complexity Analysis of Primal-Dual Newton Methods for P *(κ) Linear Complementarity Problems. In: Frenk, H., Roos, K., Terlaky, T., Zhang, S. (eds) High Performance Optimization. Applied Optimization, vol 33. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3216-0_10

Download citation

  • DOI: https://doi.org/10.1007/978-1-4757-3216-0_10

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-4819-9

  • Online ISBN: 978-1-4757-3216-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics