Exponential Decay of Sensitivity in Graph-Structured Nonlinear Programs

نویسندگان

چکیده

We study solution sensitivity for nonlinear programs (NLPs) whose structures are induced by graphs. These NLPs arise in many applications such as dynamic optimization, stochastic optimization with partial differential equations, and network optimization. show that a given pair of nodes, the primal-dual at one node against data perturbation other decays exponentially respect to distance between these two nodes on graph. In words, moves away from point. This result, which we call exponential decay sensitivity, holds under strong second-order sufficiency condition linear independence constraint qualification. also present conditions rate remains uniformly bounded; this allows us characterize behavior defined over subgraphs infinite The theoretical developments illustrated numerical examples.

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ژورنال

عنوان ژورنال: Siam Journal on Optimization

سال: 2022

ISSN: ['1095-7189', '1052-6234']

DOI: https://doi.org/10.1137/21m1391079