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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.
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。
In this program, the optimization method of "Conjugate Gradient-Least Squares" is employed, since it usually gives good convergent results.
程序中采用了“共轭梯度——最小二乘”优化方法，其收敛性能较好，在较坏的初值情况下也能较快收敛。
And the three optimization problems are solved respectively by the conjugate gradient method, the adaptive bivariate shrinking and the gradient descent method.
并提出分别采用共轭梯度法、二元自适应收缩法以及梯度下降法对以上优化问题求解。
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