Chaotic ant swarm for graph coloring

We present a hybrid chaotic ant swarm approach for the graph coloring problem (CASCOL). This approach is based on a novel swarm intelligence technique called chaotic ant swarm (CAS) and a simple greedy sequential coloring, First-Fit algorithm. We use the CAS evolutionary to improve First-Fit algorit...

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Bibliographic Details
Published in2010 IEEE International Conference on Intelligent Computing and Intelligent Systems Vol. 1; pp. 512 - 516
Main Authors Fangzhen Ge, Zhen Wei, Yiming Tian, Zhenjin Huang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2010
Subjects
Chaotic ant swarm
Combinational optimization
Economics
First-Fit algorithm
Generators
Graph coloring problem
Tin
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ISBN9781424465828
1424465826
DOI10.1109/ICICISYS.2010.5658530

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Summary:We present a hybrid chaotic ant swarm approach for the graph coloring problem (CASCOL). This approach is based on a novel swarm intelligence technique called chaotic ant swarm (CAS) and a simple greedy sequential coloring, First-Fit algorithm. We use the CAS evolutionary to improve First-Fit algorithm for GCP and formulate hybrid algorithm architecture. Computational experiments give evidence that our proposed algorithm is competitive with the existing algorithms for this problem.
ISBN:9781424465828
1424465826
DOI:10.1109/ICICISYS.2010.5658530