PREACO: A fast ant colony optimization for codebook generation

CNU IR > College of Smart Living > Dept. of Multimedia and Game Development > Periodical Articles > Item 310902800/27904

Please use this identifier to cite or link to this item: https://ir.cnu.edu.tw/handle/310902800/27904

Title:	PREACO: A fast ant colony optimization for codebook generation
Authors:	Tsai, Chun-Wei Tseng, Shih-Pang Yang, Chu-Sing Chiang, Ming-Chao
Contributors:	資訊多媒體應用系
Keywords:	Ant Colony Optimization Codebook Generation Problem Pattern Reduction
Date:	2013-06
Issue Date:	2014-05-26 10:48:24 (UTC+8)
Publisher:	Elsevier Science Bv
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. (C) 2013 Elsevier B. V. All rights reserved.
Relation:	Applied Soft Computing, v.13 n.6, pp.3008-3020
Appears in Collections:	[Dept. of Multimedia and Game Development] Periodical Articles

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML	1699	View/Open