On Estimation Algorithms vs Approximation Algorithms

Author Uriel Feige



PDF
Thumbnail PDF

File

LIPIcs.FSTTCS.2008.1767.pdf
  • Filesize: 448 kB
  • 7 pages

Document Identifiers

Author Details

Uriel Feige

Cite As Get BibTex

Uriel Feige. On Estimation Algorithms vs Approximation Algorithms. In IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science. Leibniz International Proceedings in Informatics (LIPIcs), Volume 2, pp. 357-363, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008) https://doi.org/10.4230/LIPIcs.FSTTCS.2008.1767

Abstract

In a combinatorial optimization problem, when given an input
instance, one seeks a feasible solution that optimizes the value
of the objective function. Many combinatorial optimization
problems are NP-hard. A way of coping with NP-hardness is by
considering approximation algorithms. These algorithms run in
polynomial time,  and their performance is measured by their
approximation ratio: the worst case ratio between the value of the
solution produced and the value of the (unknown) optimal solution.

In some cases the design of approximation algorithms includes a
nonconstructive component. As a result, the algorithms become
estimation algorithms rather than approximation algorithms: they
allow one to estimate the value of the optimal solution, without
actually producing a solution whose value is close to optimal.

We shall present a few such examples, and discuss some open
questions.

Subject Classification

Keywords
  • Estimation Algorithms
  • Approximation Algorithms
  • Combinatorial Optimization

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail