Multiobjective local search for community detection in networks
Detecting communities is of great importance in the study of complex networks. In this study, the community detection problem is formulated as a multiobjective optimization problem; then a local search-based multiobjective optimization algorithm is proposed. In the proposed algorithm, different obje...
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| Veröffentlicht in: | Soft computing (Berlin, Germany) Germany), 2016-08, Vol.20 (8), p.3273-3282 |
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| creator | Zhou, Yalan Wang, Jiahai Luo, Ningbo Zhang, Zizhen |
| description | Detecting communities is of great importance in the study of complex networks. In this study, the community detection problem is formulated as a multiobjective optimization problem; then a local search-based multiobjective optimization algorithm is proposed. In the proposed algorithm, different objectivewise local searches are designed for different objectives. These simple but effective local searches cooperate to simultaneously optimize two objectives. Extensive experiments on both synthetic and real-world networks show that the proposed algorithm obtains better or competitive results compared with existing state-of-the-art algorithms. |
| doi_str_mv | 10.1007/s00500-015-1706-5 |
| format | Article |
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| subjects | Algorithms Archives & records Artificial Intelligence Computational Intelligence Control Decomposition Engineering Genetic algorithms Mathematical Logic and Foundations Mechatronics Methodologies and Application Modularity Multiple objective analysis Networks Optimization Optimization algorithms Robotics Searching Social networks |
| title | Multiobjective local search for community detection in networks |
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