| Título: | A hybrid k-Mean-GRASP for partition based Clustering of two-dimensional data space as an application of p-median problem |
| Autores: |
Nadella, Sunil; Associate Professor,P.G. Dept of Computer Science,
Ideal College of Arts & Sciences,
Kakinada M V S V, Kiranmai; Lecturer ,Department of CSE,University College of Engineering,JNTU Kakinada Gugulotu, Narasimha; Department of CSE JNTUH College of Engineering, Nachupally, Kondagattu,Karimnagar |
| Fecha: | 2012-06-12 |
| Publicador: | International journal of computer and electronics research |
| Fuente: |
 |
| Tipo: | Peer-reviewed Article |
| Tema: |
Clustering; GRASP; Metaheuristic; construction phase and Improvement phase Computer Science & Engineering |
| Descripción: | The most widespread facility location paradigm is the p-median problem. It is a paradigm known NP-Hard and combinatorial optimization problem. In different application areas the facility location modeling is extensively used. It is used in marketing to analyze customers and for network establishment in cellular tower arrangement which serves maximum clients, in computer networks and in many other areas. Metaheuristic plays an important role in many areas like Operations Research, Algorithm analysis, Data Mining etc. In this paper a new clustering algorithm k-Mean-GRASP (Greedy Randomized Adaptive Search Procedure) is proposed, which determines the number of clusters of user choice similar to k-means, and follows metaheuristic approach. Generally, Metaheuristic is a two phase iterative method. So, the proposed algorithm is also encompassed with two phases. First phase ascertains the cluster of user specified number using k-means algorithm. At this stage the resultant cluster is considered as a best cluster. The second phase strives for the improvement of the cluster so obtained in the first phase. In the proposed work the first phase is termed as Construction phase which makes use of k-Means algorithm and the second phase as Enhancement phase. Our empirical results put forward that the proposed k-Mean-GRASP clustering algorithm outperforms the other methods. Clustering is the process of dividing the points into similar groups. The proposed method can also be used as a clustering algorithm based on the nature of the p-median problem. |
| Idioma: | Inglés |
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