An Enhanced ACO Algorithm with Pair Matching Strategy for the Longest Common Subsequence Problem

Abstract

The longest common subsequence (LCS) can indicate globally identical relationship among input sequences. The k-LCS problem tries to find the LCS of k sequences, and it becomes difficult if the length and the number of sequences are large. This paper adopts the pair matching strategy with ant colony optimization (ACO) algorithm for improving the performance of finding LCS. It requires less computational time than the hybrid algorithm of genetic algorithm (GA) and ACO algorithm. In the experiments, our method has better performance than other algorithms, including expansion algorithm, best next for maximal available symbol algorithm, GA, ACO algorithm and the hybrid algorithm of GA and ACO algorithm.

6 Figures and Tables

Cite this paper

@inproceedings{Weng2010AnEA, title={An Enhanced ACO Algorithm with Pair Matching Strategy for the Longest Common Subsequence Problem}, author={Hsiang-Yi Weng and Shyue-Horng Shiau and Chang-Biau Yanga and Yung-Hsing Peng and Kuo-Si Huang}, year={2010} }