PREACO: A fast ant colony optimization for codebook generation

Chun Wei Tsai, Shih Pang Tseng, Chu Sing Yang, Ming Chao Chiang

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)


This paper presents an effective and efficient method for speeding up ant colony optimization (ACO) in solving the codebook generation problem. The proposed method is inspired by the fact that many computations during the convergence process of ant-based algorithms are essentially redundant and thus can be eliminated to boost their convergence speed, especially for large and complex problems. To evaluate the performance of the proposed method, we compare it with several state-of-the-art metaheuristic algorithms. Our simulation results indicate that the proposed method can significantly reduce the computation time of ACO-based algorithms evaluated in this paper while at the same time providing results that match or outperform those ACO by itself can provide.

Original languageEnglish
Pages (from-to)3008-3020
Number of pages13
JournalApplied Soft Computing Journal
Issue number6
Publication statusPublished - 2013

All Science Journal Classification (ASJC) codes

  • Software


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