Particle swarm optimization (PSO) has been employed on several optimization problems, including the clustering problem. PSO has also been employed in the clustering of data of different structure and dimensionality. In this paper it is employed in the clustering of nucleic acid sequences. The application of clustering, as a statistical tool, in the analysis of data of varied complexity has been...

The K-Means algorithm is the widely used clustering technique. The performance ofthe K-Means algorithm depends highly on original cluster centers and converges to local minima. This paper proposes hybrid Artificial Fish Swarm Means (AFSK-Means) based clustering algorithm, by combining Particle Swarm Optimization with K-Means (PSOK) and Artificial Fish Swarm Algorithm based K-Means (AFSA). The b...

the simultaneous optimization of multiple responses is an important problem in the design of industrial processes in order to achieve improved quality. in this paper, we present a new metaheuristic approach including simulated annealing and particle swarm optimization to optimize all responses simultaneously. for the purpose of illustration and comparison, the proposed approach is applied to tw...

In the field of economics and business, the ever increasing amount of text documents written in different languages and the ever increasing dependence of people and organisations on such information require effective document retrieval, searching and classification mechanisms. Searching for groups of related documents has an important role in text mining and Document Management Systems. Swarm i...

This paper puts forward a new automatic clustering algorithm based on Multi-Objective Particle Swarm Optimization and Simulated Annealing, "MOPSOSA". The proposed algorithm is capable of automatic clustering which is appropriate for partitioning datasets to a suitable number of clusters. MOPSOSA combines the features of the multi-objective based particle swarm optimization (PSO) and the Multi-O...

regarding the large number of developed particle swarm optimization (pso) algorithms and the various applications for which pso has been used, selecting the most suitable variant of pso for solving a particular optimization problem is a challenge for most researchers. in this paper, using a comprehensive survey and taxonomy on different types of pso, an expert system (es) is designed to identif...

Location problem of multi-distribution center is a kind of NP hard problem. To solve such problems, this paper proposes a chaos adaptive mutation particle swarm optimization algorithm. The algorithm uses the ergodic property of chaos to initialize the particle swarm to enhance the diversity of the population, according to the variance of population fitness to adjust the probability of mutation,...

Nowadays data growth is directly proportional to time and it is a major challenge to store the data in an organised fashion. Document clustering is the solution for organising relevant documents together. In this paper, a web clustering algorithm namely WDC-KABC is proposed to cluster the web documents effectively. The proposed algorithm uses the features of both K-means and Artificial Bee Colo...