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| A Novel Genetic Algorithm for Global Optimization | |
| 作者姓名： | Chun-feng WANG Kui LIU Pei-ping SHEN |
| 作者单位： | College of Mathematics and Information.Henan Normal University;Henan Engineering Laboratory for Big Data Statistical Analysis and Optimal Control |
| 基金项目： | supported by the National Natural Science Foundation NSFC(11671122);the Key Project of Henan Educational Committee(19A110021.19A510014). |
| 摘 要： | This paper presents a novel genetic algorithm for globally solving un-constraint optimization problem.In this algorithm,a new real coded crossover operator is proposed firstly.Furthermore,for improving the convergence speed and the searching ability of our algorithm,the good point set theory rather than random selection is used to generate the initial population,and the chaotic search operator is adopted in the best solution of the current iteration.The experimental results tested on numerical benchmark functions show that this algorithm has excellent solution quality and convergence characteristics,and performs better than some algorithms. |
| 关 键 词： | GENETIC algorithm GOOD point set CHAOTIC SEARCH CONTINUOUS optimization |
A Novel Genetic Algorithm for Global Optimization |
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| Chun-feng WANG,Kui LIU,Pei-ping SHEN.A Novel Genetic Algorithm for Global Optimization[J].Acta Mathematicae Applicatae Sinica,2020,36(2):482-491. | |
| Authors: | Wang Chun-feng Liu Kui Shen Pei-ping |
| Institution: | 1.College of Mathematics and Information, Henan Normal University, Xinxiang, 453007, China ;2.Henan Engineering Laboratory for Big Data Statistical Analysis and Optimal Control, School of Mathematics and Information Sciences, Henan Normal University, Xinxiang, 453007, China ; |
| Abstract: | Acta Mathematicae Applicatae Sinica, English Series - This paper presents a novel genetic algorithm for globally solving un-constraint optimization problem. In this algorithm, a new real coded... |
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