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Exact penalization of mathematical programs with equilibrium constraints

机译:具有平衡约束的数学程序的精确惩罚

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摘要

We study theoretical and computational aspects of an exact penalization approach to mathematical programs with equilibrium constraints (MPECs). In the first part, we prove that a Mangasarian-Fromovitz-type condition ensures the existence of a stable local error bound at the root of a real-valued nonnegative piecewise smooth function. A specification to nonsmooth formulations of equilibrium constraints, e.g., complementarity conditions or normal equations, provides conditions which guarantee the existence of a nonsmooth exact penalty function for MPECs. In the second part, we study a trust region minimization method for a class of composite nonsmooth functions which comprises exact penalty functions arising from MPECs. We prove a global convergence result for the general method and incorporate a penalty update rule. A further specification results in an SQP trust region method for MPECs based on an l_1 penalty function.
机译:我们研究具有平衡约束(MPEC)的数学程序的精确惩罚方法的理论和计算方面。在第一部分中,我们证明了Mangasarian-Fromovitz型条件可确保在实值非负分段光滑函数的根处存在稳定的局部误差。对平衡约束的非光滑公式(例如互补条件或正态方程)的规范提供了保证存在MPEC的非光滑精确罚函数的条件。在第二部分中,我们研究了一类组合非光滑函数的信任区域最小化方法,该函数包括MPEC产生的精确惩罚函数。我们证明了该通用方法的全局收敛性结果,并纳入了惩罚更新规则。进一步的规范导致基于l_1惩罚函数的MPEC的SQP信任域方法。

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