Network improvement problems

PDF Version Also Available for Download.

Description

The authors study budget constrained optimal network improvement problems. Such problems aim at finding optimal strategies for improving a network under some cost measure subject to certain budget constraints. As an example, consider the following prototypical problem: Let G = (V, E) be an undirected graph with two cost values L(e) and C(e) associated with each edge e, where L(e) denotes the length of e and C(e) denotes the cost of reducing the length of e by a unit amount. A reduction strategy specifies for each edge e, the amount by which L(e) is to be reduced. For a given ... continued below

Physical Description

15 p.

Creation Information

Krumke, S.O.; Noltemeier, H.; Drangmeister, K.U.; Marathe, M.V. & Ravi, S.S. September 1, 1995.

Context

This article is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this article can be viewed below.

Who

People and organizations associated with either the creation of this article or its content.

Authors

Sponsor

Publisher

Provided By

UNT Libraries Government Documents Department

Serving as both a federal and a state depository library, the UNT Libraries Government Documents Department maintains millions of items in a variety of formats. The department is a member of the FDLP Content Partnerships Program and an Affiliated Archive of the National Archives.

Contact Us

What

Descriptive information to help identify this article. Follow the links below to find similar items on the Digital Library.

Description

The authors study budget constrained optimal network improvement problems. Such problems aim at finding optimal strategies for improving a network under some cost measure subject to certain budget constraints. As an example, consider the following prototypical problem: Let G = (V, E) be an undirected graph with two cost values L(e) and C(e) associated with each edge e, where L(e) denotes the length of e and C(e) denotes the cost of reducing the length of e by a unit amount. A reduction strategy specifies for each edge e, the amount by which L(e) is to be reduced. For a given budget B, the goal is to find a reduction strategy such that the total cost of reduction is at most B and the minimum cost tree (with respect to some measure M) under the modified L costs is the best over all possible reduction strategies which obey the budget constraint. Typical measures M for a tree are the total weight and the diameter. They provide both hardness and approximation results for the two measures M mentioned above. For the problem of minimizing the total weight of a spacing tree, they provide an algorithm that, for any fixed {gamma},{var_epsilon} > 0, finds a solution whose weight is at most (1 + 1/{gamma}) times that of a minimum length spanning tree plus an additive constant of at most {var_epsilon} and the total cost of improvement is at most (1 + {gamma}) times the budget B. This result can be extended to obtain approximation algorithms for more general network design problems considered in [GW, GG+94].

Physical Description

15 p.

Notes

OSTI as DE96000030

Source

  • ACM symposium on discrete algorithms, Atlanta, GA (United States); Paderborn (Germany), Jan 1995; Jul 1996

Language

Item Type

Identifier

Unique identifying numbers for this article in the Digital Library or other systems.

  • Other: DE96000030
  • Report No.: LA-UR--95-2925
  • Report No.: CONF-9501107--1;CONF-960769--1
  • Grant Number: W-7405-ENG-36
  • Office of Scientific & Technical Information Report Number: 106605
  • Archival Resource Key: ark:/67531/metadc620989

Collections

This article is part of the following collection of related materials.

Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

What responsibilities do I have when using this article?

When

Dates and time periods associated with this article.

Creation Date

  • September 1, 1995

Added to The UNT Digital Library

  • June 16, 2015, 7:43 a.m.

Description Last Updated

  • Feb. 25, 2016, 9:50 p.m.

Usage Statistics

When was this article last used?

Yesterday: 0
Past 30 days: 0
Total Uses: 1

Interact With This Article

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

Citations, Rights, Re-Use

Krumke, S.O.; Noltemeier, H.; Drangmeister, K.U.; Marathe, M.V. & Ravi, S.S. Network improvement problems, article, September 1, 1995; New Mexico. (digital.library.unt.edu/ark:/67531/metadc620989/: accessed December 16, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.