Fischer-Burmeister-based Multiplier Dynamics in Inequality-Constrained Optimization

We study proportional-integral multiplier feedback for inequality-constrained optimization using the Fischer-Burmeister complementarity residual. We construct explicit dynamics and characterize gain-dependent stability and convergence rates. For a single active constraint, we derive exact local stability and decay-rate conditions, including a tradeoff between continuous-time convergence and discretization costs. For strongly convex objectives with affine constraints, we establish global convergence and characterize geometric conditions for uniform exponential stability. Numerical experiments compare feedback structures and computational costs.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-11-02
DOI
https://doi.org/10.48550/arxiv.2611.02991
Primary Topic
Optimization and Variational Analysis
Type
preprint
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preprint

Fischer-Burmeister-based Multiplier Dynamics in Inequality-Constrained Optimization

Kang Liu, Jianchen Hu
arXiv (Cornell University)
Optimization and Variational Analysis
preprint

Fischer-Burmeister-based Multiplier Dynamics in Inequality-Constrained Optimization

Kang Liu, Jianchen Hu
preprint en

Abstract

We study proportional-integral multiplier feedback for inequality-constrained optimization using the Fischer-Burmeister complementarity residual. We construct explicit dynamics and characterize gain-dependent stability and convergence rates. For a single active constraint, we derive exact local stability and decay-rate conditions, including a tradeoff between continuous-time convergence and discretization costs. For strongly convex objectives with affine constraints, we establish global convergence and characterize geometric conditions for uniform exponential stability. Numerical experiments compare feedback structures and computational costs.

arXiv (Cornell University)
Optimization and Variational Analysis
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Fischer-Burmeister-based Multiplier Dynamics in Inequality-Constrained Optimization — Kang Liu, Jianchen Hu · arXiv (Cornell University) (2026) | TGRS Research Map | TGRS