activity
20232026
collaborators

9 papers

math.OC2026

An Improved Lower Bound for the Three-Dimensional Blaschke--Lebesgue Problem from Spectral and Dual Perspectives

Akatsuki Nishioka

The Blaschke--Lebesgue problem asks for convex bodies of minimum volume among all convex bodies of prescribed constant width. In the plane, the minimizer is the Reuleaux triangle,…

math.OC2025

Revisiting Invex Functions: Explicit Kernel Constructions and Characterizations

Akatsuki Nishioka

An invex function generalizes a convex function in the sense that every stationary point is a global minimizer. Recently, invex functions and their subclasses have attracted attent…

math.OC2025

A class of nonconvex semidefinite programming in which every KKT point is globally optimal

Akatsuki Nishioka, Yoshihiro Kanno

We consider a special class of nonconvex semidefinite programming problems and show that every point satisfying the Karush--Kuhn--Tucker (KKT) conditions is globally optimal despit…

math.OC2025

Pseudo-concave optimization of the first eigenvalue of elliptic operators with application to topology optimization by homogenization

Akatsuki Nishioka

We study optimization problems for the first eigenvalue of a linear elliptic operator. As applications, we consider homogenized two-phase optimal design problems, also known as top…

math.OC2024

Variational analysis of unbounded and discontinuous generalized eigenvalue functions with application to topology optimization

Akatsuki Nishioka, Yoshihiro Kanno

The maximum (or minimum) generalized eigenvalue of symmetric positive semidefinite matrices that depend on optimization variables often appears as objective or constraint functions…

math.OC2024

A unified Euler--Lagrange system for analyzing continuous-time accelerated gradient methods

Mitsuru Toyoda, Akatsuki Nishioka, Mirai Tanaka

This paper presents an Euler--Lagrange system for a continuous-time model of the accelerated gradient methods in smooth convex optimization and proposes an associated Lyapunov-func…