3 papers
math.OC2026
Augmented Lagrangian methods for convex optimization with priority constraints via an infeasibility control framework
Yuya Yamakawa, Shota Yamanaka, Nobuo Yamashita
We consider convex optimization problems with prioritized equality constraints, which may be infeasible. In many applications, such as network optimization and image reconstruction…
math.OC2026
An uncertainty model for positive-valued parameters with application to robust optimization
Tatsuya Tanaka, Huimin Li, Shota Yamanaka +2
Many practical optimization problems involve uncertain parameters that are strictly positive. However, the most common uncertainty sets used in robust optimization are the box and…
math.OC2025
A strong second-order sequential optimality condition for nonlinear programming problems
Huimin Li, Yuya Yamakawa, Ellen H. Fukuda +1
Most numerical methods developed for solving nonlinear programming problems are designed to find points that satisfy certain optimality conditions. While the Karush-Kuhn-Tucker con…