The study on an improved Genetic Algorithm
| Authors: | He Dakuo, Key Laboratory of Process Industry Automation, Ministry of Education, Northeastern University, China
Wang Fuli, Key Laboratory of Process Industry Automation, Ministry of Education, Northeastern University, China
Jia Mingxing, Key Laboratory of Process Industry Automation, Ministry of Education, Northeastern University, China |
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| Topic: | 3.2 Cognition and Control ( AI, Fuzzy, Neuro, Evolut.Comp.) |
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| Session: | Soft Computing for Control |
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| Keywords: | hybrid coding，binary encoding，real encoding，accelerated operator，hybrid coding genetic algorithm(HCGA) |
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Abstract
By the analysis of the performance of binary encoding and real encoding and the characteristics of the optimization process, hybrid coding is proposed by combining binary encoding and real encoding. Hybrid coding synthesizes the advantage of both binary encoding and real encoding and maintains the accuracy of the algorithm. Accelerated operator based on line search is introduced to improve the searching speed of genetic algorithms. A hybrid coding genetic algorithm is proposed, which is used to solve nonlinear optimization problems. The results of simulation indicate that the new algorithm has good accuracy and capability of dealing with the constraints.
