A New Algorithm for Multi-objective Graph Partitioning

Abstract

Recently, a number of graph partitioning applications have emerged with additional requirements that the traditional graph partitioning model alone cannot effectively handle. One such class of problems is those in which multiple objectives, each of which can be modeled as a sum of weights of the edges of a graph, must be simultaneously optimized. This class of problems can be solved utilizing a multi-objective graph partitioning algorithm. We present a new formulation of the multi-objective graph partitioning problem and describe an algorithm that computes partitionings with respect to this formulation. We explain how this algorithm provides the user with a fine-tuned control to the tradeoffs amount the objectives, results in predictable partitionings, and is able to handle both similar and dissimilar objectives.

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Document Details

Document Type
Technical Report
Publication Date
Sep 21, 1999
Accession Number
AD1020025

Entities

People

  • George Karypis
  • Kirk Schloegel
  • Vipin Kumar

Organizations

  • University of Minnesota

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Algorithms
  • Computations
  • Computer Science
  • Computers
  • Distributed Computing
  • Engineering
  • Equations
  • Fuzzy Logic
  • Fuzzy Sets
  • High Performance Computing
  • Multiobjective Optimization
  • New York
  • Optimization
  • Parallel Computing
  • Parallel Processing
  • Sparse Matrix
  • Universities

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Graph Algorithms and Convex Optimization.
  • Systems Analysis and Design