6 papers
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…
Second-order cone programming for distributionally robust compliance optimization of trusses considering input distribution uncertainty
Takumi Fujiyama, Yoshihiro Kanno
Reliability-based design optimization (RBDO) is a methodology for designing systems and components under the consideration of probabilistic uncertainty. In practical engineering, t…
Data-driven confidence bound for structural response using segmented least squares: a mixed-integer programming approach
Yoshihiro Kanno
As one of data-driven approaches to computational mechanics in elasticity, this paper presents a method finding a bound for structural response, taking uncertainty in a material da…
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…
A feasible smoothing accelerated projected gradient method for nonsmooth convex optimization
Akatsuki Nishioka, Yoshihiro Kanno
Smoothing accelerated gradient methods achieve faster convergence rates than that of the subgradient method for some nonsmooth convex optimization problems. However, Nesterov's ext…
On a minimization problem of the maximum generalized eigenvalue: properties and algorithms
Akatsuki Nishioka, Mitsuru Toyoda, Mirai Tanaka +1
We study properties and algorithms of a minimization problem of the maximum generalized eigenvalue of symmetric-matrix-valued affine functions, which is nonsmooth and quasiconvex,…