Genetic Algorithms and Grouping Problems
Genetic Algorithms and Grouping Problems
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Information Retrieval
Multi-objective evolutionary algorithms: introducing bias among Pareto-optimal solutions
Advances in evolutionary computing
Proceedings of the 2004 ACM symposium on Applied computing
Discovering patterns in spatial data using evolutionary programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Multiobjective data clustering
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
A novel multi-objective genetic algorithm for clustering
IDEAL'11 Proceedings of the 12th international conference on Intelligent data engineering and automated learning
MOEA for clustering: comparison of mutation operators
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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A new dynamic clustering method using multi-objective evolutionary algorithm is proposed. As opposed to the traditional static clustering algorithms, our method implements variable length chromosome which allows the algorithm to search for both optimal cluster center positions and cluster number. Thus the cluster number is optimized during run time dynamically instead of being pre-specified as a parameter. We also introduce two complementary objective functions–compactness and connectedness instead of one single objective. To optimize the two measures simultaneously, the NSGA-II, a highly efficient multi-objective evolutionary algorithm, is adapted for the clustering problem. The simultaneous optimization of these objectives improves the quality of the resulting clustering of problems with different data properties. At last, we apply our algorithm on several real data sets from the UCI machine learning repository and obtain good results.