A variant of EAM to uncover community structure in complex networks

作     者：Singh, Tribhuvan Mishra, Krishn Kumar Ranvijay 

作者机构：MNNIT Allahabad Dept Comp Sci & Engn Prayagraj India 

出 版 物：《INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION》 (国际生物启发计算杂志)

年 卷 期：2020年第16卷第2期

页      面：102-110页

核心收录：

学科分类：0710[理学-生物学] 07[理学] 09[农学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：single-objective optimisation evolutionary algorithms environmental adaptation method EAM community detection problem 

摘      要：Environmental adaptation method (EAM) was developed to solve single-objective optimisation problems. After the first proposal, other variants have been suggested to speed up the convergence rate and to maintain the diversity of the solutions. Among those variants, IEAM-RP works with real numbers. In this paper, a variant of IEAM-RP has been suggested with major changes in adaptation operator to improve the overall performance of the algorithm. In the proposed method, significant attention has been given for balancing exploration and exploitation of individuals in the population. The performance of the proposed algorithm is compared against 14 state-of-the-art algorithms using standard benchmark functions of the comparing continuous optimisers (COCO) framework. Further, to check the effectiveness of the proposed approach, it has been applied to a real-world problem of community detection in complex networks. Again, the experimental results are found very promising and competitive compared to other algorithms.