跳到主要导航 跳到搜索 跳到主要内容

An improvement to ant colony optimization heuristic

  • Shaoxing University
  • China Jiliang University

科研成果: 书/报告/会议事项章节会议稿件同行评审

5 引用 (Scopus)

摘要

Ant Colony Optimization (ACO) heuristic provides a relatively easy and direct method to handle problem's constraints (through introducing the so called solution construction process), while in the other heuristics, constraint-handling is normally sophisticated. But this makes its solving process slow for the solution construction process occupies most part of its computation time. In this paper, we propose a strategy to hybridize Hopfield discrete neural networks (HDNN) with ACO heuristic for maximum independent set (MIS) problems. Several simulation instances showed that the strategy can greatly improve ACO heuristic performance not only in time cost but also in solution quality.

源语言英语
主期刊名Advances in Neural Networks - ISNN 2008 - 5th International Symposium on Neural Networks, ISNN 2008, Proceedings
出版商Springer Verlag
816-825
页数10
版本PART 1
ISBN(印刷版)3540877312, 9783540877318
DOI
出版状态已出版 - 2008
活动5th International Symposium on Neural Networks, ISNN 2008 - Beijing, 中国
期限: 24 9月 200828 9月 2008

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
编号PART 1
5263 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议5th International Symposium on Neural Networks, ISNN 2008
国家/地区中国
Beijing
时期24/09/0828/09/08

学术指纹

探究 'An improvement to ant colony optimization heuristic' 的科研主题。它们共同构成独一无二的学术指纹。

引用此