An Inexact Sequential Quadratic Optimization Algorithm for Nonlinear Optimization
An Inexact Sequential Quadratic Optimization Algorithm for Nonlinear Optimization
复制标题
一种非线性优化的不精确序贯二次优化算法
DOI：
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发表时间：
2014
影响因子：
3.1
通讯作者：
A. Wächter
中科院分区：
文献类型：
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作者：
Frank E. Curtis;T. C. Johnson;Daniel P. Robinson;A. Wächter
提出了一种求解具有等式和不等式约束的非线性优化问题的序列二次优化方法。该算法的新颖之处在于，在每次迭代过程中，允许原始-对偶搜索方向是给定的二次优化子问题的不精确解。我们给出了搜索方向(即不精确子问题解)必须满足的一组一般的、宽松的条件，从而保证了求解该非线性问题的算法的全局收敛。该算法可以看作是一种全局收敛的不精确牛顿算法。数值实验结果验证了所提数值方法的可靠性。
We propose a sequential quadratic optimization method for solving nonlinear optimization problems with equality and inequality constraints. The novel feature of the algorithm is that, during each iteration, the primal-dual search direction is allowed to be an inexact solution of a given quadratic optimization subproblem. We present a set of generic, loose conditions that the search direction (i.e., inexact subproblem solution) must satisfy so that global convergence of the algorithm for solving the nonlinear problem is guaranteed. The algorithm can be viewed as a globally convergent inexact Newton-based method. The results of numerical experiments are provided to illustrate the reliability of the proposed numerical method.