A scalable deterministic annealing algorithm for resource allocation problems

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we develop a scalable algorithm for solving resource allocation problems on large datasets. The algorithm is based on the deterministic annealing (DA) algorithm presented in [6]. The capability of the DA algorithm to identify clusters at successive iteration steps is exploited to truncate certain large computations in the algorithm. These truncations are obtained by recursively grouping the clusters into appropriate groups and running the DA algorithm, in parallel, on the groups. This paper develops a notion of interaction between groups which is used to measure the deviation of this algorithm from the DA algorithm. Simulations are presented that show significant improvements in the computational time while keeping the error in resource allocations within prespecified tolerance limits.

Original languageEnglish (US)
Title of host publicationProceedings of the 2006 American Control Conference
Pages3092-3097
Number of pages6
StatePublished - Dec 1 2006
Event2006 American Control Conference - Minneapolis, MN, United States
Duration: Jun 14 2006Jun 16 2006

Publication series

NameProceedings of the American Control Conference
Volume2006
ISSN (Print)0743-1619

Other

Other2006 American Control Conference
Country/TerritoryUnited States
CityMinneapolis, MN
Period6/14/066/16/06

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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