数学
惩罚法
序列二次规划
数学优化
分段
缩小
互补性(分子生物学)
功能(生物学)
趋同(经济学)
信任域
应用数学
二次规划
数学分析
计算机科学
生物
进化生物学
遗传学
经济
经济增长
半径
计算机安全
作者
Stefan Scholtes,Michael Stöhr
出处
期刊:Siam Journal on Control and Optimization
[Society for Industrial and Applied Mathematics]
日期:1999-01-01
卷期号:37 (2): 617-652
被引量:136
标识
DOI:10.1137/s0363012996306121
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 \(\ell_1\) penalty function.
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