Abstract
This paper presents a concurrent-hybrid evolutionary algorithm by integrating the improved differential evolution algorithm and multi-mutation competition algorithm based on the culture algorithm framework. This concurrent hybrid evolutionary algorithm has been applied to geometric constraint optimization problem. The experimental results indicate that the performance of the proposed algorithm is excellent in the ability of global solution searching and stability, and this algorithm can find the optimal solution quickly.
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Zhang, Y., Liu, K., Liu, G., Zhao, Z. (2010). A Concurrent-Hybrid Evolutionary Algorithm for Geometric Constraint Solving. In: Cai, Z., Tong, H., Kang, Z., Liu, Y. (eds) Computational Intelligence and Intelligent Systems. ISICA 2010. Communications in Computer and Information Science, vol 107. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16388-3_1
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DOI: https://doi.org/10.1007/978-3-642-16388-3_1
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