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Journal of Applied Sciences
  Year: 2008 | Volume: 8 | Issue: 15 | Page No.: 2695-2702
DOI: 10.3923/jas.2008.2695.2702
 
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A Hybrid Evolutionary Algorithm Based on ACO and SA for Cluster Analysis
T. Niknam, J. Olamaei and B. Amiri

Abstract:
This study presents an efficient hybrid evolutionary optimization algorithm based on combining Ant Colony Optimization (ACO) and Simulated Annealing (SA), called ACO-SA, for optimal clustering N object into K clusters. The new ACO-SA algorithm is tested on several data sets and its performance is compared with those of ACO, SA and K-means clustering. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for data clustering.
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How to cite this article:

T. Niknam, J. Olamaei and B. Amiri, 2008. A Hybrid Evolutionary Algorithm Based on ACO and SA for Cluster Analysis. Journal of Applied Sciences, 8: 2695-2702.

DOI: 10.3923/jas.2008.2695.2702

URL: https://scialert.net/abstract/?doi=jas.2008.2695.2702

 
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