Cost function and factor demand estimation and measurement are among the most useful tools in economic analysis. This paper defines cost function flexibility in a new way that extends results and concepts from consumer demand theory to models of joint production. This applies to production models where input demand equations can be represented in terms of input prices, quasi-fixed inputs, and c...

The linear-quadratic (LQ) optimization is a close to standard technique in the optimal control framework. LQ is very well researched and there are many extensions for more sophisticated scenarios like nonlinear models. Usually, the quadratic objective function is taken as a prerequisite for calculating derivative-based solutions of optimal control problems. However, it is not clear whether this...

This paper deals with two kinds of the one-dimensional global optimization problems over a closed finite interval: (i) the objective function f(x) satisfies the Lipschitz condition with a constant L; (ii) the first derivative of f(x) satisfies the Lipschitz condition with a constant M . In the paper, six algorithms are presented for the case (i) and six algorithms for the case (ii). In both cas...

Wedescribe a polynomial-size conic quadratic reformulation for amachine-job assignment problemwith separable convex cost. Because the conic strengthening is based only on the objective of the problem, it can also be applied to other problems with similar cost functions. Computational results demonstrate the effectiveness of the conic reformulation. © 2009 Elsevier B.V. All rights reserved.

Support vector machine (SVM) is a popular classification technique which classifies data using a max-margin separator hyperplane. The normal vector and bias of the mentioned hyperplane is determined by solving a quadratic model implies that SVM training confronts by an optimization problem. Among of the extensions of SVM, cost-sensitive scheme refers to a model with multiple costs which conside...

— For given positive integers a, b, q we investigate the density of solutions (x, y) ∈ Z to congruences ax+ by ≡ 0 mod q.

In this research paper, the problem of optimization of quadratic forms associated with the dynamics of Hopfield-Amari neural network is considered. An elegant (and short) proof of the states at which local/global minima of quadratic form are attained is provided. A theorem associated with local/global minimization of quadratic energy function using the HopfieldAmari neural network is discussed....

Quadratic programming (QP) is an optimization problem wherein one minimizes (or maximizes) a quadratic function of a finite number of decision variable subject to a finite number of linear inequality and/ or equality constraints. In this paper, a quadratic programming problem (FFQP) is considered in which all cost coefficients, constraints coefficients, and right hand side are characterized by ...

ÐThe robust Huber M-estimator, a differentiable cost function that is quadratic for small errors and linear otherwise, is modeled exactly, in the original primal space of the problem, by an easily solvable simple convex quadratic program for both linear and nonlinear support vector estimators. Previous models were significantly more complex or formulated in the dual space and most involved spec...