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A conjugate gradient method with quasi-Newton approximation

Jonas Koko (2000)

Applicationes Mathematicae

The conjugate gradient method of Liu and Storey is an efficient minimization algorithm which uses second derivatives information, without saving matrices, by finite difference approximation. It is shown that the finite difference scheme can be removed by using a quasi-Newton approximation for computing a search direction, without loss of convergence. A conjugate gradient method based on BFGS approximation is proposed and compared with existing methods of the same class.

A consumption-investment problem modelled as a discounted Markov decision process

Hugo Cruz-Suárez, Raúl Montes-de-Oca, Gabriel Zacarías (2011)

Kybernetika

In this paper a problem of consumption and investment is presented as a model of a discounted Markov decision process with discrete-time. In this problem, it is assumed that the wealth is affected by a production function. This assumption gives the investor a chance to increase his wealth before the investment. For the solution of the problem there is established a suitable version of the Euler Equation (EE) which characterizes its optimal policy completely, that is, there are provided conditions...

A continuous optimization model for a joint problem of pricing and resource allocation

Mustapha Bouhtou, Guillaume Erbs (2009)

RAIRO - Operations Research

This paper investigates the problem of maximizing the revenue of a telecommunications operator by simultaneously pricing point-to-point services and allocating bandwidth in its network, while facing competition. Customers are distributed into market segments, i.e., groups of customers with a similar preference for the services. This preference is expressed using utility functions, and customers choose between the offers of the operator and of the competition according to their utility. We model...

A cooperative sensor network : optimal deployment and functioning

Alfonso Farina, Antonio Graziano, Francesca Mariani, Francesco Zirilli (2010)

RAIRO - Operations Research - Recherche Opérationnelle

A network of mobile cooperative sensors is considered. The following problems are studied: (1) the “optimal“deployment of the sensors on a given territory; (2) the detection of local anomalies in the noisy data measured by the sensors. In absence of an information fusion center in the network, from “local” interactions between sensors “global“solutions of these problems are found.

A Cooperative Sensor Network: Optimal Deployment and Functioning

Alfonso Farina, Antonio Graziano, Francesca Mariani, Francesco Zirilli (2011)

RAIRO - Operations Research

A network of mobile cooperative sensors is considered. The following problems are studied: (1) the “optimal" deployment of the sensors on a given territory; (2) the detection of local anomalies in the noisy data measured by the sensors. In absence of an information fusion center in the network, from “local" interactions between sensors “global" solutions of these problems are found.

A DEA model for two-stage parallel-series production processes

Alireza Amirteimoori, Feng Yang (2014)

RAIRO - Operations Research - Recherche Opérationnelle

Data envelopment analysis (DEA) has been widely used to measure the performance of the operational units that convert multiple inputs into multiple outputs. In many real world scenarios, there are systems that have a two-stage network process with shared inputs used in both stages of productions. In this paper, the problem of evaluating the efficiency of a set of specialized and interdependent components that make up a large DMU is considered. In these processes the first stage consists of two parallel...

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