This paper deals with generalized vector quasi-equilibrium problems. Using a so-called nonlinear scalarization function and a fixed point theorem, existence theorems for two classes of generalized vector quasi-equilibrium problems are established. Copyright Springer-Verlag 2005

LetZ be a compact set of the real space ℜ with at leastn + 2 points;f,h1,h2:Z → ℜ continuous functions,h1,h2 strictly positive andP(x,z),x≔(x <Subscript>0</Subscript>,...,x <Subscript> n </Subscript>)<Superscript>τ</Superscript> ε ℜ<Superscript> n+1</Superscript>,z ε ℜ, a polynomial of degree at mostn. Consider a feasible setM ≔ {x ε ℜ<Superscript> n+1</Superscript>∣∀z εZ, −h <Subscript>2</Subscript>(z) ≤P(x,...</subscript></superscript></superscript></superscript></subscript></subscript>

We give a generic regularity condition under which each weakly efficient decision making unit in the CCR model of data envelopment analysis is also CCR-efficient. Then we interpret the problem of finding maximal parameters which preserve efficiency of CCR-efficient DMUs under directional...

We consider nonlinear stochastic optimization problems with probabilistic constraints. The concept of a p-efficient point of a probability distribution is used to derive equivalent problem formulations, and necessary and sufficient optimality conditions. We analyze the dual functional and its...

The floorplanning (or facility layout) problem consists in finding the optimal positions for a given set of modules of fixed area (but perhaps varying height and width) within a facility such that the distances between pairs of modules that have a positive connection cost are minimized. This is...

For an optimization problem with a composed objective function and composed constraint functions we determine, by means of the conjugacy approach based on the perturbation theory, some dual problems to it. The relations between the optimal objective values of these duals are studied. Moreover,...

Conjugate function theory is used to develop dual programs for nonseparable convex programs involving the square root function. This function arises naturally in finance when one measures the risk of a portfolio by its variance–covariance matrix, in stochastic programming under chance...