Self-Adaptive Genetic Algorithm for Clustering

Clustering is a hard combinatorial problem which has many applications in science and practice. Genetic algorithms (GAs) have turned out to be very effective in solving the clustering problem. However, GAs have many parameters, the optimal selection of which depends on the problem instance. We introduce a new self-adaptive GA that finds the parameter setup on-line during the execution of the algorithm. In this way, the algorithm is able to find the most suitable combination of the available components. The method is robust and achieves results comparable to or better than a carefully fine-tuned non-adaptive GA.

[1]  Olli Nevalainen,et al.  Genetic Algorithms for Large-Scale Clustering Problems , 1997, Comput. J..

[2]  Olli Nevalainen,et al.  Tabu search algorithm for codebook generation in vector quantization , 1998, Pattern Recognit..

[3]  Brian Everitt,et al.  Cluster analysis , 1974 .

[4]  Jeng-Shyang Pan,et al.  VQ codebook design using genetic algorithms , 1995 .

[5]  Ali S. Hadi,et al.  Finding Groups in Data: An Introduction to Chster Analysis , 1991 .

[6]  Allen Gersho,et al.  Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.

[7]  J. H. Ward.  Hierarchical Grouping to Optimize an Objective Function , 1963 .

[8]  K. Zeger,et al.  Stochastic relaxation algorithm for improved vector quantiser design , 1989 .

[9]  Zbigniew Michalewicz,et al.  Adaptation in evolutionary computation: a survey , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[10]  Pasi Fränti,et al.  Randomised Local Search Algorithm for the Clustering Problem , 2000, Pattern Analysis & Applications.

[11]  Olli Nevalainen,et al.  Iterative split-and-merge algorithm for vector quantization codebook generation , 1998 .

[12]  Pasi Fränti,et al.  Genetic algorithm with deterministic crossover for vector quantization , 2000, Pattern Recognit. Lett..

[13]  Pasi Fr.  Genetic algorithm with deterministic crossover for vector quantization , 2000 .

[14]  M. Verlaan,et al.  Classification of Binary Vectors by Stochastic Complexity , 1997 .

[15]  V. Delport,et al.  Genetic algorithm for codebook design in vector quantisation , 1995 .

[16]  William Equitz,et al.  A new vector quantization clustering algorithm , 1989, IEEE Trans. Acoust. Speech Signal Process..

[17]  P. Fränti,et al.  Iterative split-and-merge algorithm for VQ codebook generation , 1998 .

[18]  Olli Nevalainen,et al.  A fast exact GLA based on code vector activity detection , 2000, IEEE Trans. Image Process..

[19]  Robert C. Kohberger,et al.  Cluster Analysis (3rd ed.) , 1994 .

[20]  J. MacQueen.  Some methods for classification and analysis of multivariate observations , 1967 .

[21]  Olli Nevalainen,et al.  On the splitting method for vector quantization codebook generation , 1997 .