PREACO: A fast ant colony optimization for codebook generation

Authors:
Chun-Wei Tsai;Shih-Pang Tseng;Chu-Sing Yang;Ming-Chao Chiang
Affiliations:
Department of Applied Informatics and Multimedia, Chia Nan University of Pharmacy & Science, Tainan 71710, Taiwan, ROC;Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung 80424, Taiwan, ROC;Department of Electrical Engineering, National Cheng Kung University, Tainan 70101, Taiwan, ROC;Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung 80424, Taiwan, ROC
Venue:
Applied Soft Computing
Year:
2013

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Abstract

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.