34 citations · 147 across the 20 of their papers we have counts for
21 papers
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…
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…
Riemannian conditional gradient methods for composite optimization problems
Kangming Chen, Ellen H. Fukuda
In this paper, we propose Riemannian conditional gradient methods for minimizing composite functions, i.e., those that can be expressed as the sum of a smooth function and a retrac…
Adaptive generalized conditional gradient method for multiobjective optimization
Anteneh Getachew Gebrie, Ellen Hidemi Fukuda
In this paper, we propose a generalized conditional gradient method for multiobjective optimization, which can be viewed as an improved extension of the classical Frank-Wolfe (cond…
A second-order sequential optimality condition for nonlinear second-order cone programming problems
Ellen H. Fukuda, Kosuke Okabe
In the last two decades, the sequential optimality conditions, which do not require constraint qualifications and allow improvement on the convergence assumptions of algorithms, ha…
Nonlinear conjugate gradient method for vector optimization on Riemannian manifolds with retraction and vector transport
Kangming Chen, Ellen H. Fukuda, Hiroyuki Sato
In this paper, we propose nonlinear conjugate gradient methods for vector optimization on Riemannian manifolds. The concepts of Wolfe and Zoutendjik conditions are extended for Rie…