In this paper, we solve an inverse problem arising in convex optimization. We consider a maximization problem under m linear constraints. We characterize the solutions of this kind of problems. More precisely, we give necessary and sufficient conditions for a given function in Rn to be the solution of a multi-constraint maximization problem. The conditions we give here extend well-known results in microeconomic theor
summary:The characterization of the solution set of a convex constrained problem is a well-known att...
Conventionally, in an optimization problem, we aim to determine the values of the decision variables...
AbstractContinuing our papers (Optimization 18, 1987, 485–499; and Math. Oper. Stat. Ser. Optim. 11,...
In this paper, we study inverse optimization problems defined as follows: Let S denote the set of fe...
"(Revised January 27, 1998)"--T.p. -- "February 1998."--Cover.Includes bibliographical references (p...
AbstractA minimization problem for a matrix-valued matrix function is considered. A duality theorem ...
AbstractIn this paper we provide a duality theory for multiobjective optimization problems with conv...
Most inverse optimization models impute unspecified parameters of an objective function to make an o...
Most inverse optimization models impute unspecified parameters of an objective function to make an o...
AbstractIn this paper we provide a duality theory for multiobjective optimization problems with conv...
We consider an extension of a linear model studied by Gale, Kuhn and Tucker (GKT) for an optimizatio...
The problem of minimizing a twice differentiable convex function f is considered, subject to Ax = b,...
2000 Mathematics Subject Classification: Primary 90C29; Secondary 49K30.In this paper, we establish ...
summary:The characterization of the solution set of a convex constrained problem is a well-known att...
Abstract. We consider linear inverse problems where the solution is assumed to fulfill some general ...
summary:The characterization of the solution set of a convex constrained problem is a well-known att...
Conventionally, in an optimization problem, we aim to determine the values of the decision variables...
AbstractContinuing our papers (Optimization 18, 1987, 485–499; and Math. Oper. Stat. Ser. Optim. 11,...
In this paper, we study inverse optimization problems defined as follows: Let S denote the set of fe...
"(Revised January 27, 1998)"--T.p. -- "February 1998."--Cover.Includes bibliographical references (p...
AbstractA minimization problem for a matrix-valued matrix function is considered. A duality theorem ...
AbstractIn this paper we provide a duality theory for multiobjective optimization problems with conv...
Most inverse optimization models impute unspecified parameters of an objective function to make an o...
Most inverse optimization models impute unspecified parameters of an objective function to make an o...
AbstractIn this paper we provide a duality theory for multiobjective optimization problems with conv...
We consider an extension of a linear model studied by Gale, Kuhn and Tucker (GKT) for an optimizatio...
The problem of minimizing a twice differentiable convex function f is considered, subject to Ax = b,...
2000 Mathematics Subject Classification: Primary 90C29; Secondary 49K30.In this paper, we establish ...
summary:The characterization of the solution set of a convex constrained problem is a well-known att...
Abstract. We consider linear inverse problems where the solution is assumed to fulfill some general ...
summary:The characterization of the solution set of a convex constrained problem is a well-known att...
Conventionally, in an optimization problem, we aim to determine the values of the decision variables...
AbstractContinuing our papers (Optimization 18, 1987, 485–499; and Math. Oper. Stat. Ser. Optim. 11,...