工程混合离散变量优化设计的遗传算法及应用

The Genetic Optimization Algorithm of Engineering Optimal Design with Mixed Discrete Variables and Its Application

针对机械工程中的非线性约束优化的混合离散变量优化设计问题 ,提出了一种新的遗传算法。该方法在遗传算法中通过去掉等式约束、构造字符型编码向量、精心设计动态遗传及变异算子等改造操作 ,较大地提高了寻优效率和寻化能力 ,并用Matlab语言开发了相应软件。实例表明 ,该方法正确 ,算法简洁、稳健 ,求解精度和可靠性高 。

A new improved genetic optimization algorithm(IGOA) is proposed for solving nonlinear constraint problem of mechanical engineering with mixed discrete variables. After removig equation constraint,constructing character-type coding vectors and well-connected planning dynamic inherit and aberrance operator and so on. This new algorithm can speed up the rate of convergence and improve the ability of solution. The soft-ware is developed with Matlab language. The calculation example proved that the method is successful,simple and moderate,and it has high rate of convergence,accuracy and reliability. It is also effective for the mechanical optimization problem.