Constrained Ant Colony Optimization for Data Clustering

Processes that simulate natural phenomena have successfully been applied to a number of problems for which no simple mathematical solution is known or is practicable. Such meta-heuristic algorithms include genetic algorithms, particle swarm optimization and ant colony systems and have received increasing attention in recent years. This paper extends ant colony systems and discusses a novel data clustering process using Constrained Ant Colony Optimization (CACO). The CACO algorithm extends the Ant Colony Optimization algorithm by accommodating a quadratic distance metric, the Sum of K Nearest Neighbor Distances (SKNND) metric, constrained addition of pheromone and a shrinking range strategy to improve data clustering. We show that the CACO algorithm can resolve the problems of clusters with arbitrary shapes, clusters with outliers and bridges between clusters.

[1]  Jeng-Shyang Pan,et al.  Bound for Minkowski metric or quadratic metric applied to VQ codeword search , 1996 .

[2]  Anne Brindle,et al.  Genetic algorithms for function optimization , 1980 .

[3]  George Karypis,et al.  C HAMELEON : A Hierarchical Clustering Algorithm Using Dynamic Modeling , 1999 .

[4]  Jiawei Han,et al.  CLARANS: A Method for Clustering Objects for Spatial Data Mining , 2002, IEEE Trans. Knowl. Data Eng..

[5]  Ickjai Lee,et al.  AUTOCLUST+: Automatic Clustering of Point-Data Sets in the Presence of Obstacles , 2000, TSDM.

[6]  Johannes Gehrke,et al.  CACTUS—clustering categorical data using summaries , 1999, KDD '99.

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

[8]  Hilarie K. Orman,et al.  Activating Networks: A Progress Report , 1999, Computer.

[9]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[10]  Hans-Peter Kriegel,et al.  A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.

[11]  Cheng-Fa Tsai,et al.  A new data clustering approach for data mining in large databases , 2002, Proceedings International Symposium on Parallel Architectures, Algorithms and Networks. I-SPAN'02.

[12]  Shusaku Tsumoto,et al.  Foundations of Intelligent Systems, 15th International Symposium, ISMIS 2005, Saratoga Springs, NY, USA, May 25-28, 2005, Proceedings , 2005, ISMIS.

[13]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

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

[15]  J. A. Bland.  Space-planning by ant colony optimisation , 1999 .

[16]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[17]  Tian Zhang,et al.  BIRCH: an efficient data clustering method for very large databases , 1996, SIGMOD '96.

[18]  Vipin Kumar,et al.  Chameleon: Hierarchical Clustering Using Dynamic Modeling , 1999, Computer.

[19]  Jeng-Shyang Pan,et al.  Ant colony system with communication strategies , 2004, Inf. Sci..

[20]  Aidong Zhang,et al.  WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases , 1998, VLDB.

[21]  John F. Roddick,et al.  Temporal, Spatial, and Spatio-Temporal Data Mining , 2001, Lecture Notes in Computer Science.

[22]  Sudipto Guha,et al.  CURE: an efficient clustering algorithm for large databases , 1998, SIGMOD '98.

[23]  Jeng-Shyang Pan,et al.  Parallel Ant Colony Systems , 2003, ISMIS.

[24]  Philip S. Yu,et al.  Redefining Clustering for High-Dimensional Applications , 2002, IEEE Trans. Knowl. Data Eng..

[25]  Vittorio Maniezzo,et al.  The Ant System Applied to the Quadratic Assignment Problem , 1999, IEEE Trans. Knowl. Data Eng..

[26]  D. Frank Hsu,et al.  Proceedings International Symposium On Parallel Architectures, Algorithms And Networks , 2000, Proceedings International Symposium on Parallel Architectures, Algorithms and Networks. I-SPAN 2000.

[27]  Alex Alves Freitas,et al.  Data mining with an ant colony optimization algorithm , 2002, IEEE Trans. Evol. Comput..