Optimality Conditions for Minimizers at Infinity in Polynomial Programming
@article{Pham2017OptimalityCF, title={Optimality Conditions for Minimizers at Infinity in Polynomial Programming}, author={Tien Son Pham}, journal={Math. Oper. Res.}, year={2017}, volume={44}, pages={1381-1395} }
In this paper we study necessary optimality conditions for the optimization problem $$\textrm{infimum}f_0(x) \quad \textrm{ subject to } \quad x \in S,$$ where $f_0 \colon \mathbb{R}^n \rightarrow \mathbb{R}$ is a polynomial function and $S \subset \mathbb{R}^n$ is a set defined by polynomial inequalities. Assume that the problem is bounded below and has the Mangasarian--Fromovitz property at infinity. We first show that if the problem does {\em not} have an optimal solution, then a version at…
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References
SHOWING 1-10 OF 33 REFERENCES
A Frank–Wolfe type theorem for nondegenerate polynomial programs
- MathematicsMath. Program.
- 2014
If f0 is bounded from below on S, then f0 attains its infimum on S and f_0, the optimal solution to the constrained polynomial optimization problem, is studied.
Minima of Functions of Several Variables with Inequalities as Side Conditions
- Mathematics
- 2014
The problem of determining necessary conditions and sufficient conditions for a relative minimum of a function \( f({x_1},{x_2},....,{x_n})\) in the class of points \( x = ({x_1},{x_2},....,{x_n})\)…
Well-Posedness in Unconstrained Polynomial Optimization Problems
- MathematicsSIAM J. Optim.
- 2016
There exists an open and dense semialgebraic set $\mathcal{U}_{\Gamma}$ in the corresponding Euclidean space of data such that for every polynomial f, which is bounded from below on R, the problem of minimization of f over R is strongly well-posed.
Global Hölderian Error Bound for Nondegenerate Polynomials
- MathematicsSIAM J. Optim.
- 2013
It is proved that if f is convenient and nondegenerate with respect to its Newton boundary at infinity in the sense of Kouchnirenko, then it has a global Holderian error bound.
On Extensions of the Frank-Wolfe Theorems
- MathematicsComput. Optim. Appl.
- 1999
This paper first proves a general continuity result for the solution set defined by a system of convex quadratic inequalities, and proves that the optimal solution set is nonempty.
On Generalizations of the Frank-Wolfe Theorem to Convex and Quasi-Convex Programmes
- MathematicsComput. Optim. Appl.
- 2006
It is proved that the optimal solution set of the considered problem is nonempty, this way extending the attainability result well known as the so-called Frank-Wolfe theorem.
The Fritz John Necessary Optimality Conditions in the Presence of Equality and Inequality Constraints
- Mathematics
- 1967
Coercive Polynomials and Their Newton Polytopes
- MathematicsSIAM J. Optim.
- 2015
This article analyzes the coercivity on f in $\mathbb{R}^n$ of multivariate polynomials in terms of their so-called Newton polytopes at infinity in the broad class ofSo-called gem regular polynoms and characterize their coercivity via conditions solely containing information about the geometry of the vertex set of the Newton polytope at infinity, as well as sign conditions on the corresponding polynomial coefficients.
On the bifurcation set of a polynomial function and Newton boundary, II
- Mathematics
- 1990
Let /: C-*C be a polynomial function. It is well known that there exists a finite set TgC, such that /: C\f-(F^C\r is a locally trivial fibration (see [1], [5], [13], [15], [16]). The smallest such…
A Frank–Wolfe Type Theorem for Convex Polynomial Programs
- MathematicsComput. Optim. Appl.
- 2002
It is shown that an arbitrary quadratic function f attains its minimum over a nonempty convex polyhedral set X provided f is bounded from below over X and that a similar statement holds if f is a convex polynomial and X is the solution set of a system of convexPolynomial inequalities.