Skip to main content
SpringerLink
Log in

A polynomial time approximation scheme for dense MupIN 2S{upAT}

  • Conference paper
  • First Online:
Fundamentals of Computation Theory (FCT 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1684))

Included in the following conference series:

Abstract

It is proved that everywhere-dense MupIN 2SupAT and everywhere- dense MupIN EupQ both have polynomial time approximation schemes.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight 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. S. Arora, D. Karger, M. Karpinski, Polynomial time approximation schemes for dense instances of NP-hard problems, Proc. of 27th STOC, 1995, 284–293. The full paper will appear in Journal of Computer and System Sciences.

    Google Scholar 

  2. W. Fernandez de la Vega, Max-Cut has a Randomized Approximations Scheme in Dense Graphs, Random Structures and Algorithms, 8(3) (1996), 187–198.

    Article  MATH  MathSciNet  Google Scholar 

  3. N. Garg, V. V. Vazirani and M. Yannakakis, Approximate max-flow min-(multi)cut theorems and their applications, SIAM Journal on Computing 25 (1996), 235–251.

    Article  MATH  MathSciNet  Google Scholar 

  4. O. Goldreich, S. Goldwasser and D. Ron, Property Testing and its Connection to Learning and Approximation, Proc. of 37th IEEE FOCS, 1996, 339–348. The full paper has appeared in Journal of the ACM, 45 (4) (1998), 653–750.

    Google Scholar 

  5. M. Karpinski, Polynomial Time Approximation Schemes for Some Dense Instances of NP-Hard Optimization Problems, Randomization and Approximation Techniques in Computer Science, LNCS 1269, 1–14.

    Google Scholar 

  6. C. Papadimitriou and M. Yannakakis, Optimization, Approximation and Complexity Classes, Journal of Computer and System Science 43 (1991), 425–440.

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Universitè Paris-Sud, LRI, bât.490, F-91405, Orsay, France

    Cristina Bazgan

  2. CNRS, UMR 8623, Universitè Paris-Sud, LRI, F-91405, Orsay, France

    W. de la Fernandez Vega

Authors
  1. Cristina Bazgan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. W. de la Fernandez Vega
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Faculty of Computer Science, “A.I.Cuza” University, 6600, Iaşi, Romania

    Gabriel Ciobanu

  2. Institute of Mathematics of the Romanian Academy, P.O. Box 1-764, 70700, Bucharest, Romania

    Gheorghe Păun

Rights and permissions

Reprints and permissions

Copyright information

© 1999 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bazgan, C., de la Fernandez Vega, W. (1999). A polynomial time approximation scheme for dense MupIN 2S{upAT} . In: Ciobanu, G., Păun, G. (eds) Fundamentals of Computation Theory. FCT 1999. Lecture Notes in Computer Science, vol 1684. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48321-7_6

Download citation

  • DOI: https://doi.org/10.1007/3-540-48321-7_6

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66412-3

  • Online ISBN: 978-3-540-48321-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation