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The Ethereal
Edge-set reduction to efficiently solve the graph partitioning problem with the genetic algorithm
July 19, 2023 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Ali Chaouche, Menouar Boulif
arXiv ID
2307.10410
Category
cs.NE: Neural & Evolutionary
Cross-listed
math.OC
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
The graph partitioning problem (GPP) is among the most challenging models in optimization. Because of its NP-hardness, the researchers directed their interest towards approximate methods such as the genetic algorithms (GA). The edge-based GA has shown promising results when solving GPP. However, for big dense instances, the size of the encoding representation becomes too huge and affects GA's efficiency. In this paper, we investigate the impact of modifying the size of the chromosomes on the edge based GA by reducing the GPP edge set. We study the GA performance with different levels of reductions, and we report the obtained results.
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