| 摘 要: 以遗传算法原理和方法为基础，简要介绍其工具箱在Matlab中的两种调用方式。在惩罚函数的基础上应用 遗传算法工具箱解决约束非线性规划问题。比较最佳适应度及最佳个体与传统数值计算方法的误差，得出遗传算法在该 类问题上可以跳出局部最优解，且收敛速度快，编写方式灵活的结论。为工程领域的推广及普及应用提供参考依据。 |
| 关键词: 遗传算法；约束非线性规划；惩罚函数；图形用户 |
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中图分类号: TP301
文献标识码: A
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| Application of the MATLAB Genetic Algorithm Toolbox in Constrained Nonlinear Penalty Functions |
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YUAN Mingzhu
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(Productivity Centre of Jiangsu Province, Nanjing 210000, China )
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| Abstract: Based on the principles and methods of the genetic algorithm,the paper briefly introduces two kinds of toolbox methods in Matlab.The genetic algorithm toolbox is applied to solve constrained nonlinear programming problems based on penalty functions.The optimal fitness and the errors between the best individual and the traditional numerical method are compared.It is concluded that the genetic algorithms can jump out of the local optimal solutions with high convergence rates and flexible writing methods.This study provides reference to promote and generalize its application in the engineering field. |
| Keywords: genetic algorithms;constrained nonlinear programming;penalty functions;graphical user |
