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Combinatorial particle swarm optimization (CPSO) for partitional clustering problem
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DOI：10.1016/j.amc.2007.03.010.png)
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This paper presents a new clustering approach based on the combinatorial particle swarm optimization (CPSO) algorithm. Each particle is represented as a string of length n (where n is the number of data points) the ith element of the string denotes the group number assigned to object i. An integer vector corresponds to a candidate solution to the clustering problem. A swarm of particles are initiated and fly through the solution space for targeting the optimal solution. To verify the efficiency of the proposed CPSO algorithm, comparisons with a genetic algorithm are performed. Computational results show that the proposed CPSO algorithm is very competitive and outperforms the genetic algorithm. (C) 2007 Elsevier Inc. All rights reserved.
Keyword:
particle swarm optimization
combinatorial particle swarm optimization
genetic algorithms
partitional clustering
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3.4
论文数:
2.3W
被引数:
3.3W
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