Abstract
An evolutionary circle detection method based on a novel Chaotic Hybrid Algorithm (CHA) is proposed. The method combines the strengths of particle swarm optimization, genetic algorithms and chaotic dynamics, and involves the standard velocity and position updating rules of PSO with the ideas of GA selection, crossover and mutation. In addition, the notion of species is introduced into the proposed CHA to enhance its performance in solving multimodal problems. The effectiveness of the Species based Chaotic Hybrid Algorithm (SCHA) is proven through simulations and benchmarking, and finally, it is successfully applied to solve circle detection problems.
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Wu, CH., Dong, N., Ip, WH., Chan, CY., Yung, KL., Chen, ZQ. (2010). Chaotic Hybrid Algorithm and Its Application in Circle Detection. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2010. Lecture Notes in Computer Science, vol 6024. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12239-2_31
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DOI: https://doi.org/10.1007/978-3-642-12239-2_31
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