Stability and Error Analysis for Optimization and Generalized Equations

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Authors
Royset, Johannes O.
Advisors
Second Readers
Subjects
Hausdorff distance
approximation theory
stability
perturbation analysis
generalized equations
optimality conditions
Date of Issue
2020
Date
Publisher
Society for Industrial and Applied Mathematics (SIAM)
Language
Abstract
Stability and error analysis remain challenging for problems that lack regularity properties near solutions, are subject to large perturbations, and might be infinite-dimensional. We consider nonconvex optimization and generalized equations defined on metric spaces and develop bounds on solution errors using the truncated Hausdorff distance applied to graphs and epigraphs of the underlying set-valued mappings and functions. In the process, we extend the calculus of such distances to cover compositions and other constructions that arise in nonconvex problems. The results are applied to constrained problems with feasible sets that might have empty interiors, solution of KKT systems, and optimality conditions for difference-of-convex functions and composite functions.
Type
Article
Description
The article of record as published may be found at https://doi.org/10.1137/19M1251424
Department
Operations Research (OR)
Organization
Identifiers
NPS Report Number
Sponsors
This work was supported in part by DARPA (Lagrange) under grant HR0011-8- 34187, by the ONR (Science of Autonomy) under grant N0001419WX00183, and by the AFOSR (Optimization and Discrete Mathematics) under grant F4FGA08272G001.
Funding
This work was supported in part by DARPA (Lagrange) under grant HR0011-8- 34187, by the ONR (Science of Autonomy) under grant N0001419WX00183, and by the AFOSR (Optimization and Discrete Mathematics) under grant F4FGA08272G001.
Format
29 p.
Citation
Royset, Johannes O. "Stability and Error Analysis for Optimization and Generalized Equations." SIAM Journal on Optimization 30.1 (2020): 752-780.
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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