Tahereh Hassanzadeh

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In this paper, a new evolutionary optimization model, called CLA-FA, is proposed. This new model is a combination of a model called cellular learning automata (CLA) and the Firefly Algorithm (FA). In the proposed algorithm, at first we modify the firefly algorithm to improve the efficiency of this algorithm then we use this algorithm with CLA. in the(More)
The firefly algorithm (FA), which is usually used in optimization problems, is a stochastic, population-based algorithm inspired by the intelligent, collective behavior of fireflies in nature. In the standard FA, each firefly in each neighborhood is compared with other fireflies, and the less-bright firefly moves toward the brighter one (in the maximization(More)
Data clustering is a common technique for data analysis and is used in many fields, including data mining, pattern recognition and image analysis. K-means clustering is a common and simple approach for data clustering but this method has some limitation such as local optimal convergence and initial point sensibility. Firefly algorithm is a swarm based(More)
Firefly Algorithm is an evolutionary algorithm based on collective intelligence and derived from nature. This algorithm is mainly used in solving optimization problems. In this paper, to increase the power and accuracy of the algorithm and to improve the results, an improved firefly algorithm by changing the movement of fireflies and using of global optima(More)
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