We consider the convex optimization problem P: minx{f(x): x ∈ K} where f is convex continuously differentiable, and K ⊂ Rn is a com-pact convex set with representation {x ∈ Rn: gj(x) ≥ 0, j = 1,...,m} for some continuously differentiable functions (gj). We discuss the case where the gj ’s are not all concave (in contrast with convex programming where they all are). In particular, even if the gj are not concave, we consider the log-barrier function φµ with parameter µ, associated with P, usually defined for concave functions (gj). We then show that any limit point of any sequence (xµ) ⊂ K of stationary points of φµ, µ → 0, is a Karush-Kuhn-Tucker point of problem P and a global minimizer of f on K
AbstractThe Kuhn–Tucker type necessary optimality conditions are given for the problem of minimizing...
It is known that there are feasible algorithms for minimizing convex functions, and that for general...
It is known that there are feasible algorithms for minimizing convex functions, and that for general...
7 pages; 1 figureInternational audienceWe consider the convex optimization problem P: min { f(x): x ...
7 pages; 1 figureInternational audienceWe consider the convex optimization problem P: min { f(x): x ...
International audienceWe consider the convex optimization problem $\min \{ f(x) : g_j(x)\leq 0,\,j=1...
International audienceWe consider the convex optimization problem $\min \{ f(x) : g_j(x)\leq 0,\,j=1...
We investigate the minima of functionals of the form ¿gWƒ(u), where O 2 is a bounded domain and ƒ a ...
We investigate the minima of functionals of the form ¿gWƒ(u), where O 2 is a bounded domain and ƒ a ...
We investigate the minima of functionals of the form ¿gWƒ(u), where O 2 is a bounded domain and ƒ a ...
We investigate the minima of functionals of the form ¿gWƒ(u), where O 2 is a bounded domain and ƒ a ...
We investigate the minima of functionals of the form ¿gWƒ(u), where O 2 is a bounded domain and ƒ a ...
Disclaimer: These notes have not been subjected to the usual scrutiny reserved for formal publicatio...
The phrase convex optimization refers to the minimization of a convex function over a convex set. Ho...
We establish new necessary and sufficient optimality conditions for global optimization problems. In...
AbstractThe Kuhn–Tucker type necessary optimality conditions are given for the problem of minimizing...
It is known that there are feasible algorithms for minimizing convex functions, and that for general...
It is known that there are feasible algorithms for minimizing convex functions, and that for general...
7 pages; 1 figureInternational audienceWe consider the convex optimization problem P: min { f(x): x ...
7 pages; 1 figureInternational audienceWe consider the convex optimization problem P: min { f(x): x ...
International audienceWe consider the convex optimization problem $\min \{ f(x) : g_j(x)\leq 0,\,j=1...
International audienceWe consider the convex optimization problem $\min \{ f(x) : g_j(x)\leq 0,\,j=1...
We investigate the minima of functionals of the form ¿gWƒ(u), where O 2 is a bounded domain and ƒ a ...
We investigate the minima of functionals of the form ¿gWƒ(u), where O 2 is a bounded domain and ƒ a ...
We investigate the minima of functionals of the form ¿gWƒ(u), where O 2 is a bounded domain and ƒ a ...
We investigate the minima of functionals of the form ¿gWƒ(u), where O 2 is a bounded domain and ƒ a ...
We investigate the minima of functionals of the form ¿gWƒ(u), where O 2 is a bounded domain and ƒ a ...
Disclaimer: These notes have not been subjected to the usual scrutiny reserved for formal publicatio...
The phrase convex optimization refers to the minimization of a convex function over a convex set. Ho...
We establish new necessary and sufficient optimality conditions for global optimization problems. In...
AbstractThe Kuhn–Tucker type necessary optimality conditions are given for the problem of minimizing...
It is known that there are feasible algorithms for minimizing convex functions, and that for general...
It is known that there are feasible algorithms for minimizing convex functions, and that for general...