An Integrated Method Based on PSO and EDA for the Max-Cut Problem
Joint Authors
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2016, Issue 2016 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-02-18
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
The max-cut problem is NP-hard combinatorial optimization problem with many real world applications.
In this paper, we propose an integrated method based on particle swarm optimization and estimation of distribution algorithm (PSO-EDA) for solving the max-cut problem.
The integrated algorithm overcomes the shortcomings of particle swarm optimization and estimation of distribution algorithm.
To enhance the performance of the PSO-EDA, a fast local search procedure is applied.
In addition, a path relinking procedure is developed to intensify the search.
To evaluate the performance of PSO-EDA, extensive experiments were carried out on two sets of benchmark instances with 800 to 20000 vertices from the literature.
Computational results and comparisons show that PSO-EDA significantly outperforms the existing PSO-based and EDA-based algorithms for the max-cut problem.
Compared with other best performing algorithms, PSO-EDA is able to find very competitive results in terms of solution quality.
American Psychological Association (APA)
Lin, Geng& Guan, Jian. 2016. An Integrated Method Based on PSO and EDA for the Max-Cut Problem. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1099656
Modern Language Association (MLA)
Lin, Geng& Guan, Jian. An Integrated Method Based on PSO and EDA for the Max-Cut Problem. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1099656
American Medical Association (AMA)
Lin, Geng& Guan, Jian. An Integrated Method Based on PSO and EDA for the Max-Cut Problem. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1099656
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099656