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A new inexact SQP algorithm for nonlinear systems of mixed equalities and inequalities

机译:一种新的混合等式和不平等的非线性系统的新不准确SQP算法

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Traditional inexact SQP algorithm can only solve equality constrained optimization (Byrd et al. Math. Program. 122, 273-299 2010). In this paper, we propose a new inexact SQP algorithm with affine scaling technique for nonlinear systems of mixed equalities and inequalities, which arise in complementarity and variational inequalities. The nonlinear systems are transformed into a special nonlinear optimization with equality and bound constraints, and then we give a new inexact SQP algorithm for solving it. The new algorithm equipped with affine scaling technique does not require a quadratic programming subproblem with inequality constraints. The search direction is computed by solving one linear system approximately using iterative linear algebra techniques. Under mild assumptions, we discuss the global convergence. The preliminary numerical results show the effectiveness of the proposed algorithm.
机译:传统的不精确SQP算法只能解决平等约束优化(Byrd等人。数学。程序。122,273-299 2010)。 在本文中,我们提出了一种新的非线性SQP算法,其具有用于非线性和不等式的非线性系统的仿射缩放技术,其互补性和变分不等式产生。 非线性系统被转换为具有平等和束缚约束的特殊非线性优化,然后我们提供了一种解决它的新的不精确的SQP算法。 配备仿射缩放技术的新算法不需要具有不等式约束的二次编程子问题。 通过迭代线性代数技术求解一个线性系统来计算搜索方向。 在温和的假设下,我们讨论全球融合。 初步数值结果显示了所提出的算法的有效性。

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