Abstract Black-box model structures are dominated by large multivariate functions. Usually a generic basis function expansion is used, e.g. polynomial basis, and the parameters of tuned given data. This pragmatic often necessary step considering black-box nature problem. However, having identified suitable function, there no need to stick original basis. So-called decoupling techniques aim at t...

In this note we present a new concept of well-posedness for Optimization Problems with constraints described by parametric Variational Inequalities or parametric Minimum Problems. We investigate some classes of operators and functions that ensure this type of wellposedness.

The index is excellent by the Malmquist index as extended to productivity measurement. The index developed here is defined in terms of input cost rather than input quantity distance functions in supply chain. Therefore, we propose productivity change is decomposed into overall efficiency and cost technical change. These decompositions provide a clearer situation of the root sources of supply ch...

In this paper, we study the problem of minimizing the ratio of two quadratic functions subject to a quadratic constraint. First we introduce a parametric equivalent of the problem. Then a bisection and a generalized Newton-based method algorithms are presented to solve it. In order to solve the quadratically constrained quadratic minimization problem within both algorithms, a semidefinite optim...

In this paper, many formulas and identities for computing the r-parametric Hermite type polynomials are given with help of generating functions. Using functions algebraic methods, a relation is also including these 2-variable Kampé de Fériet polynomials. Moreover, relations containing two parametric Apostol-Bernoulli higher order, Apostol-Euler Apostol-Genocchi order Dickson obtained. Finally, ...

A tensor-based method is proposed for the solution of partial differential equations defined on uncertain parameterized domains. It provides an accurate solution which is explicit with respect to parameters defining the shape of the domain, thus allowing efficient a posteriori probabilistic or parametric analyses. In the proposed method, a fictitious domain approach is first adopted for the ref...

A method to solve linear fuzzy equations with a symmetric matrix is proposed. Ignoring the symmetry leads to an overestimation of the solution. Our method to find the solution of a system of linear fuzzy equations takes the symmetry of the matrix into account and is based on parametric functions. It is a practical algorithm using parametric functions in which the variables are given by elements...

Literature suggests two main approaches, parametric and non-parametric, for constructing efficiency frontiers using which efficiency scores of other units can be based. Parametric functions can be either deterministic or stochastic in nature. However, when multiple inputs and outputs are encountered, Data Envelopment Analysis (DEA), a non-parametric approach, is a powerful tool used for decades...

We present here the explicit parametric solutions of second order differential equations invariant under time translation and rescaling and third order differential equations invariant under time translation and the two homogeneity symmetries. The computation of first integrals gives in the most general case, the parametric form of the general solution. For some polynomial functions we obtain a...

In this paper, we consider the problem of computing the algebraic parametric equation of the Euclidean 1-center function in R, d ≥ 2, for a system of n static points and m mobile points having motion defined by rational parametric functions. We have shown that the corresponding Euclidean 1-center function is a piecewise differentiable function and have derived its exact parametric algebraic equ...