Abstract
The evolutionary direction based gradient of fitness of the individuals is proposed in this paper. Then the evolutionary procedure can be guided by a series of optimal evolutionary direction belongs to current population. A gradient based genetic algorithm is put forward under the description of the evolutionary direction. And lastly, with some typical test functions, the results prove the highly quality of the algorithm on precision, stability and convergence rate. And it also indicates that such improved evolutionary can greatly overcome the shortcoming of low efficiency in traditional evolutionary algorithms.
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Zhao, Zq., Gou, J., Jiang, Yl., Wang, Dx. (2009). A Genetic Algorithm Based on Evolutionary Direction. In: Cao, B., Li, TF., Zhang, CY. (eds) Fuzzy Information and Engineering Volume 2. Advances in Intelligent and Soft Computing, vol 62. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03664-4_85
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DOI: https://doi.org/10.1007/978-3-642-03664-4_85
Publisher Name: Springer, Berlin, Heidelberg
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