Hamed Asgari - Department of Computer and Information Technology Engineering Science and Research Branch, Islamic Azad University, Qazvin, Iran
Behrooz Masoumi - Department of Computer and Information Technology Engineering Qazvin Islamic Azad University Qazvin, Iran
Omid sojoodi sheijani - Department of Computer and Information Technology Engineering Qazvin Islamic Azad University Qazvin, Iran

Text summarization is the objective extraction of some parts of the text, such as sentence and paragraph, as the document abstract. If there are documents with a large amountof information, extractive text summarization would be arisen as an NP-complete problem. To solve these problems, metaheuristicalgorithms are used. In this paper, a method based on multi-agent particle swarm optimization approach is proposed toimprove the extractive text summarization. In this method, eachparticle will be upgraded with the status of multi-agent systems. The proposed method is tested on DUC 2002 standard documentsand analyzed by ROUGE evaluation software. The experimental results show that this method has better performance than other compared methods

Text summarization, Particle swarm optimization,Multi-Agent Systems, Extractive method