Abstract
An improved genetic algorithm for searching optimal parameters in n-dimensional space is presented, which encodes movement direction and distance and searches from coarse to precise. The algorithm can realize global optimization and improve the search efficiency, and can be applied effectively in industrial optimization, data mining and pattern recognition.
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Tang, B., Hu, G. An improved genetic algorithm for searching optimal parameters in n-dimensional space. J. of Electron.(China) 19, 218–219 (2002). https://doi.org/10.1007/s11767-002-0040-0
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DOI: https://doi.org/10.1007/s11767-002-0040-0