Preprint
Jul 2026
Using Subproblem Objective Gaps in Inexact Augmented Lagrangian and ADMM Algorithms, with Applications to Stochastic Mixed Integer Programming
This paper shows how bounds on subproblem objective value suboptimality can be used in inexact augmented Lagrangian methods and ADMM algorithms, and enables two new approaches to computing Lagrangian bounds on the optimal values of stochastic mixed-integer programming problems.
Jonathan Eckstein
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