M D Fajardo,S M Grad,J Vidal
M D Fajardo
We present new results on optimization problems where the involved functions are evenly convex. By means of a generalized conjugation scheme and the perturbation theory introduced by Rockafellar, we propose an alternative dual problem for a...
Radu Ioan Boţ,Ernö Robert Csetnek
Radu Ioan Boţ
In this paper, we propose two proximal-gradient algorithms for fractional programming problems in real Hilbert spaces, where the numerator is a proper, convex and lower semicontinuous function and the denominator is a smooth function, eithe...
A second-order dynamical system with Hessian-driven damping and penalty term associated to variational inequalities [0.03%]
带有Hessian阻尼和与变分不等式相关的惩罚项的二阶动力系统
Radu Ioan Boţ,Ernö Robert Csetnek
Radu Ioan Boţ
We consider the minimization of a convex objective function subject to the set of minima of another convex function, under the assumption that both functions are twice continuously differentiable. We approach this optimization problem from ...
A forward-backward penalty scheme with inertial effects for monotone inclusions. Applications to convex bilevel programming [0.03%]
具有惯性效应的单调包含向前向后惩罚方案及在凸双层编程中的应用
Radu Ioan Boţ,Dang-Khoa Nguyen
Radu Ioan Boţ
We investigate a forward-backward splitting algorithm of penalty type with inertial effects for finding the zeros of the sum of a maximally monotone operator and a cocoercive one and the convex normal cone to the set of zeroes of an another...
R Cibulka,J Preininger,T Roubal
R Cibulka
We investigate uniform versions of (metric) regularity and strong (metric) regularity on compact subsets of Banach spaces, in particular, along continuous paths. These two properties turn out to play a key role in analyzing path-following s...
An incremental mirror descent subgradient algorithm with random sweeping and proximal step [0.03%]
一种带随机遍历和次梯度的增量镜像下降算法及proximal步法
Radu Ioan Boţ,Axel Böhm
Radu Ioan Boţ
We investigate the convergence properties of incremental mirror descent type subgradient algorithms for minimizing the sum of convex functions. In each step, we only evaluate the subgradient of a single component function and mirror it back...
Inertial forward-backward methods for solving vector optimization problems [0.03%]
惯性前向-后向方法在求解向量优化问题中的应用
Radu Ioan Boţ,Sorin-Mihai Grad
Radu Ioan Boţ
We propose two forward-backward proximal point type algorithms with inertial/memory effects for determining weakly efficient solutions to a vector optimization problem consisting in vector-minimizing with respect to a given closed convex po...
New verifiable stationarity concepts for a class of mathematical programs with disjunctive constraints [0.03%]
具析取约束的数学规划的新校验驻定概念
Matúš Benko,Helmut Gfrerer
Matúš Benko
In this paper, we consider a sufficiently broad class of non-linear mathematical programs with disjunctive constraints, which, e.g. include mathematical programs with complemetarity/vanishing constraints. We present an extension of the conc...
P Hungerländer
P Hungerländer
We suggest a new variant of a row layout problem: Find an ordering of n departments with given lengths such that the total weighted sum of their distances to a given checkpoint is minimized. The Checkpoint Ordering Problem (COP) is both of ...
Non-differentiable pseudo-convex functions and duality for minimax programming problems [0.03%]
极小极大规划问题的不可微伪凸函数和对偶性
Bhatia, D.; Jain, P.
Bhatia