AbstractWe study the minimization of an M-convex function introduced by Murota. It is shown that any vector in the domain can be easily separated from a minimizer of the function. Based on this property, we develop a polynomial time algorithm
The problem of minimizing a twice differentiable convex function f is considered, subject to Ax = b,...
This paper sheds a new light on submodular function minimization and maximization from the viewpoint...
We characterize the property of obtaining a solution to a convex program by minimizing over the feas...
AbstractWe study the minimization of an M-convex function introduced by Murota. It is shown that any...
AbstractM-convex functions, introduced by Murota (Adv. Math. 124 (1996) 272; Math. Prog. 83 (1998) 3...
Abstract M-convex functions, introduced by Murota (1996, 1998), enjoy various desirable properties a...
M-convex functions, introduced by Murota (1996, 1998), enjoy various desirable properties as \discre...
AbstractA convex Fréchet differentiable function is minimized subject to a certain hyperplane at a p...
The author, in an expository paper [4], has presented an algorithm for choosing a non-negative vecto...
We investigate the minima of functionals of the form ¿gWƒ(u), where O 2 is a bounded domain and ƒ a ...
The majorization-minimization (MM) principle is an important tool for developing algorithms to solve...
A branch-and-bound method is proposed for minimizing a convex-concave function over a convex set. Th...
We present an algorithm for minimizing a convex function over all integer vectors in the plane. This...
A convex Frechet differentiable function is minimized subject to a certain´ hyperplane at a point if...
AbstractA method is proposed for the solution of minimax optimization problems in which the individu...
The problem of minimizing a twice differentiable convex function f is considered, subject to Ax = b,...
This paper sheds a new light on submodular function minimization and maximization from the viewpoint...
We characterize the property of obtaining a solution to a convex program by minimizing over the feas...
AbstractWe study the minimization of an M-convex function introduced by Murota. It is shown that any...
AbstractM-convex functions, introduced by Murota (Adv. Math. 124 (1996) 272; Math. Prog. 83 (1998) 3...
Abstract M-convex functions, introduced by Murota (1996, 1998), enjoy various desirable properties a...
M-convex functions, introduced by Murota (1996, 1998), enjoy various desirable properties as \discre...
AbstractA convex Fréchet differentiable function is minimized subject to a certain hyperplane at a p...
The author, in an expository paper [4], has presented an algorithm for choosing a non-negative vecto...
We investigate the minima of functionals of the form ¿gWƒ(u), where O 2 is a bounded domain and ƒ a ...
The majorization-minimization (MM) principle is an important tool for developing algorithms to solve...
A branch-and-bound method is proposed for minimizing a convex-concave function over a convex set. Th...
We present an algorithm for minimizing a convex function over all integer vectors in the plane. This...
A convex Frechet differentiable function is minimized subject to a certain´ hyperplane at a point if...
AbstractA method is proposed for the solution of minimax optimization problems in which the individu...
The problem of minimizing a twice differentiable convex function f is considered, subject to Ax = b,...
This paper sheds a new light on submodular function minimization and maximization from the viewpoint...
We characterize the property of obtaining a solution to a convex program by minimizing over the feas...
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