无约束优化问题的共轭梯度路径构造的思想启迪我们用其来解带线性等式约束和有界变量约束的优化问题。

The idea of conjugate gradient path in unconstrained optimization irradiates us to use this method for solving the linear equality optimization subject to bounds on variables.

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对于控制变量受箱型约束的问题，采用三角函数转换将其转化为控制无约束问题。

For boxing constraint of control, trigonometric function transformation was developed to achieve an unconstrained problem.

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通过对连续变量无约束优化、连续变量约束优化和离散变量约束优化等典型优化问题的计算分析 ，将三种惩罚函数方法进行了比较 ，指出了它们的特点及选用原则。

The selection of the key parameters and genetic operators is discussed. The calculation results of three computational examples are given. The characteristic of the three methods is pointed.

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