International audienceWe consider the problem of minimizing a functional (like the area, perimeter, surface) within the class of convex bodies whose support functions are trigonometric polynomials. The convexity constraint is transformed via the Fejer-Riesz theorem on positive trigonometric polynomials into a semidefinite programming problem. Several problems such as the minimization of the area in the class of constant width planar bodies, rotors and space bodies of revolution are revisited. The approach seems promising to investigate more difficult optimization problems in the class of three-dimensional convex bodies
In this dissertation, we study the minimization of a geometrical functional in dimension 2 and 3 und...
Semidefinite Programming (SDP) is a class of convex optimization problems with a linear objective fu...
We describe an important class of semidefinite programming problems that has received scant attentio...
International audienceWe consider the problem of minimizing a functional (like the area, perimeter, ...
International audienceThe optimization of functionals depending on shapes which have convexity, diam...
The optimization of shape functionals under convexity, diameter or constant width constraints shows...
Abstract. In this contribution we give a semi-infinite optimization approach to investigate the affi...
International audienceWe present a complete analytic parametrization of constant width bodies in dim...
Many problems of systems control theory boil down to solving polynomial equations, polynomial inequa...
In semidefinite programming one minimizes a linear function subject to the constraint that an affine...
Controlling the singular values of n-dimensional matrices is often required in geometric algorithms ...
This article proposes a new discrete framework for approximating solutions to shape optimization pro...
If K is a convex body in the Euclidean space En, we consider the six classic geometric functionals a...
Since the early 1960s, polyhedral methods have played a central role in both the theory and practice...
Our goal in this dissertation is to study some optimization problems with special structure and expl...
In this dissertation, we study the minimization of a geometrical functional in dimension 2 and 3 und...
Semidefinite Programming (SDP) is a class of convex optimization problems with a linear objective fu...
We describe an important class of semidefinite programming problems that has received scant attentio...
International audienceWe consider the problem of minimizing a functional (like the area, perimeter, ...
International audienceThe optimization of functionals depending on shapes which have convexity, diam...
The optimization of shape functionals under convexity, diameter or constant width constraints shows...
Abstract. In this contribution we give a semi-infinite optimization approach to investigate the affi...
International audienceWe present a complete analytic parametrization of constant width bodies in dim...
Many problems of systems control theory boil down to solving polynomial equations, polynomial inequa...
In semidefinite programming one minimizes a linear function subject to the constraint that an affine...
Controlling the singular values of n-dimensional matrices is often required in geometric algorithms ...
This article proposes a new discrete framework for approximating solutions to shape optimization pro...
If K is a convex body in the Euclidean space En, we consider the six classic geometric functionals a...
Since the early 1960s, polyhedral methods have played a central role in both the theory and practice...
Our goal in this dissertation is to study some optimization problems with special structure and expl...
In this dissertation, we study the minimization of a geometrical functional in dimension 2 and 3 und...
Semidefinite Programming (SDP) is a class of convex optimization problems with a linear objective fu...
We describe an important class of semidefinite programming problems that has received scant attentio...