An ant colony optimization algorithm for partitioning graphs with supply and demand

Raka Jovanovic, Milan Tuba, Stefan Voß

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

In this paper we focus on finding high quality solutions for the problem of maximum partitioning of graphs with supply and demand (MPGSD). There is a growing interest for the MPGSD due to its close connection to problems appearing in the field of electrical distribution systems, especially for the optimization of self-adequacy of interconnected microgrids. We propose an ant colony optimization algorithm for the problem. With the goal of further improving the algorithm we combine it with a previously developed correction procedure. In our computational experiments we evaluate the performance of the proposed algorithm on trees, 3-connected graphs, series-parallel graphs and general graphs. The tests show that the method manages to find optimal solutions for more than 50% of the problem instances, and has an average relative error of less than 0.5% when compared to known optimal solutions.

Original languageEnglish
Pages (from-to)317-330
Number of pages14
JournalApplied Soft Computing Journal
Volume41
DOIs
Publication statusPublished - 1 Apr 2016

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Ant colony optimization
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Keywords

  • Ant colony optimization
  • Combinatorial optimization
  • Demand vertex
  • Graph partitioning
  • Microgrid
  • Supply vertex

ASJC Scopus subject areas

  • Software

Cite this

An ant colony optimization algorithm for partitioning graphs with supply and demand. / Jovanovic, Raka; Tuba, Milan; Voß, Stefan.

In: Applied Soft Computing Journal, Vol. 41, 01.04.2016, p. 317-330.

Research output: Contribution to journalArticle

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