Eigenvalues and the max-cut problem
Ein lineares Mehrentscheidungsmodell.
Ein notwendiges und hinreichendes Optimalitätskriterium für allgemeine quadratische Optimierungsprobleme
Ein Verfahren zum Minimieren einer Funktion bei eingeschränktem Variationsbereich der Parameter.
Eine strenge Begründung dynamischer Programme und die Bestimmung ausgezeichneter Knoten- und Kantenmengen in endlichen Graphen.
El conjunto eficiente en problemas de localización con normas mixtas (Lp).
En el presente trabajo establecemos una nueva aproximación a la solución del problema de localización con normas mixtas a través de las direcciones de proyección.Probamos que el cierre octogonal de los puntos de demanda es una buena aproximación para el conjunto de puntos eficientes cuando el problema está formulado como un problema multiobjetivo con normas mixtas tipo lp. Demostramos que esta cota es alcanzable, dando condiciones para que ello ocurra, lo que es de gran importancia para el caso...
El contraste de hipótesis compuesta frente a alternativa simple como problema de programación matemática infinita.
El método de Karmarkar: un estudio de sus variantes.
En este trabajo hacemos una revisión de varias versiones del método de Karmarkar, desarrollando las ideas fundamentales propuestas por diferentes autores en relación con los aspectos más conflictivos y de mayor interés del método original.
El primer problema dual de optimización.
El problema del árbol minimal para grafos difusos.
Basándonos en algunas definiciones previas, se analiza el problema del árbol generador difuso. En primer lugar se trata su existencia y después se encuentra el árbol generador difuso de mínimo costo mediante una descomposición por α-cortes. El estudio se realiza para dos estructuras diferentes de costos.
Elements of quasiconvex subdifferential calculus.
Emotion learning: Solving a shortest path problem in an arbitrary deterministic environment in linear time with an emotional agent
The paper presents an algorithm which solves the shortest path problem in an arbitrary deterministic environment with n states with an emotional agent in linear time. The algorithm originates from an algorithm which in exponential time solves the same problem, and the agent architecture used for solving the problem is an NN-CAA architecture (neural network crossbar adaptive array). By implementing emotion learning, the linear time algorithm is obtained and the agent architecture is modified. The...
Empirical estimates in stochastic optimization via distribution tails
“Classical” optimization problems depending on a probability measure belong mostly to nonlinear deterministic optimization problems that are, from the numerical point of view, relatively complicated. On the other hand, these problems fulfil very often assumptions giving a possibility to replace the “underlying” probability measure by an empirical one to obtain “good” empirical estimates of the optimal value and the optimal solution. Convergence rate of these estimates have been studied mostly for...
Empirical regression quantile processes
We address the problem of estimating quantile-based statistical functionals, when the measured or controlled entities depend on exogenous variables which are not under our control. As a suitable tool we propose the empirical process of the average regression quantiles. It partially masks the effect of covariates and has other properties convenient for applications, e.g. for coherent risk measures of various types in the situations with covariates.
Employing different loss functions for the classification of images via supervised learning
Supervised learning methods are powerful techniques to learn a function from a given set of labeled data, the so-called training data. In this paper the support vector machines approach is applied to an image classification task. Starting with the corresponding Tikhonov regularization problem, reformulated as a convex optimization problem, we introduce a conjugate dual problem to it and prove that, whenever strong duality holds, the function to be learned can be expressed via the dual optimal solutions....
Entropic Conditions and Hedging
In many markets, especially in energy markets, electricity markets for instance, the detention of the physical asset is quite difficult. This is also the case for crude oil as treated by Davis (2000). So one can identify a good proxy which is an asset (financial or physical) (one)whose the spot price is significantly correlated with the spot price of the underlying (e.g. electicity or crude oil). Generally, the market could become incomplete. We explicit exact hedging strategies for exponential...
Entropy Based Transportation Model - a Geometric Programming Approach
Enumerating the Set of Non-dominated Vectors in Multiple Objective Integer Linear Programming
An algorithm for enumerating all nondominated vectors of multiple objective integer linear programs is presented. The method tests different regions where candidates can be found using an auxiliary binary problem for tracking the regions already explored. An experimental comparision with our previous efforts shows the method has relatively good time performance.
Énumération des chemins -minimum admissibles entre deux points
Environmentally conditioned self-reproduction