Zobrazeno 1 - 10
of 144
pro vyhledávání: '"Jiao, Liguo"'
In this paper, approximate optimality conditions and sensitivity analysis in nearly convex optimization are discussed. More precisely, as in the spirit of convex analysis, we introduce the concept of $\varepsilon$-subdifferential for nearly convex fu
Externí odkaz:
http://arxiv.org/abs/2410.04710
In this paper, we study a class of nonsmooth fractional programs {\rm (FP, for short)} with SOS-convex semi-algebraic functions. Under suitable assumptions, we derive a strong duality result between the problem (FP) and its semidefinite programming (
Externí odkaz:
http://arxiv.org/abs/2401.16716
In this paper, we focus on a class of robust vector polynomial optimization problems (RVPOP in short) without any convex assumptions. By combining/improving the utopia point method (a nonlinear scalarization) for vector optimization and "joint+margin
Externí odkaz:
http://arxiv.org/abs/2209.04885
Autor:
Guo, Feng, Jiao, Liguo
In this paper, we provide a new scheme for approximating the weakly efficient solution set for a class of vector optimization problems with rational objectives over a feasible set defined by finitely many polynomial inequalities. More precisely, we p
Externí odkaz:
http://arxiv.org/abs/2205.12863
In this paper, we are interested in the existence of Pareto solutions to vector polynomial optimization problems over a basic closed semi-algebraic set. By invoking some powerful tools from real semi-algebraic geometry, we first introduce the concept
Externí odkaz:
http://arxiv.org/abs/2109.07304
Autor:
Guo, Feng, Jiao, Liguo
In this paper, we study a class of fractional semi-infinite polynomial programming (FSIPP) problems, in which the objective is a fraction of a convex polynomial and a concave polynomial, and the constraints consist of infinitely many convex polynomia
Externí odkaz:
http://arxiv.org/abs/2008.01256
A continuous selection of polynomial functions is a continuous function whose domain can be partitioned into finitely many pieces on which the function coincides with a polynomial. Given a set of finitely many polynomials, we show that there are only
Externí odkaz:
http://arxiv.org/abs/2007.03952
Let $f$ be a real polynomial function with $n$ variables and $S$ be a basic closed semialgebraic set in $\Bbb{R}^n$. In this paper, we are interested in the problem of identifying the type (local minimizer, maximizer or not extremum point) of a given
Externí odkaz:
http://arxiv.org/abs/2004.12315
Akademický článek
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This paper aims to find efficient solutions to a multi-objective optimization problem (MP) with convex polynomial data. To this end, a hybrid method, which allows us to transform problem (MP) into a scalar convex polynomial optimization problem (P$_z
Externí odkaz:
http://arxiv.org/abs/1903.10137