973 resultados para Tabu search algorithms


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CODEX SEARCH es un motor de recuperación de información especializado en derecho de extranjería que está basado en herramientas y conocimiento lingüísticos. Un motor o Sistema de Recuperación de Información (SRI) es un software capaz de localizar información en grandes colecciones documentales (entorno no trivial) en formato electrónico. Mediante un estudio previo se ha detectado que la extranjería es un ámbito discursivo en el que resulta difícil expresar la necesidad de información en términos de una consulta formal, objeto de los sistemas de recuperación actuales. Por lo tanto, para desarrollar un SRI eficiente en el dominio indicado no basta con emplear un modelo tradicional de RI, es decir, comparar los términos de la pregunta con los de la respuesta, básicamente porque no expresan implicaciones y porque no tiene que haber necesariamente una relación 1 a 1. En este sentido, la solución lingüística propuesta se basa en incorporar el conocimiento del especialista mediante la integración en el sistema de una librería de casos. Los casos son ejemplos de procedimientos aplicados por expertos a la solución de problemas que han ocurrido en la realidad y que han terminado en éxito o fracaso. Los resultados obtenidos en esta primera fase son muy alentadores pero es necesario continuar la investigación en este campo para mejorar el rendimiento del prototipo al que se puede acceder desde &http://161.116.36.139/~codex/&.

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In this paper, we develop numerical algorithms that use small requirements of storage and operations for the computation of invariant tori in Hamiltonian systems (exact symplectic maps and Hamiltonian vector fields). The algorithms are based on the parameterization method and follow closely the proof of the KAM theorem given in [LGJV05] and [FLS07]. They essentially consist in solving a functional equation satisfied by the invariant tori by using a Newton method. Using some geometric identities, it is possible to perform a Newton step using little storage and few operations. In this paper we focus on the numerical issues of the algorithms (speed, storage and stability) and we refer to the mentioned papers for the rigorous results. We show how to compute efficiently both maximal invariant tori and whiskered tori, together with the associated invariant stable and unstable manifolds of whiskered tori. Moreover, we present fast algorithms for the iteration of the quasi-periodic cocycles and the computation of the invariant bundles, which is a preliminary step for the computation of invariant whiskered tori. Since quasi-periodic cocycles appear in other contexts, this section may be of independent interest. The numerical methods presented here allow to compute in a unified way primary and secondary invariant KAM tori. Secondary tori are invariant tori which can be contracted to a periodic orbit. We present some preliminary results that ensure that the methods are indeed implementable and fast. We postpone to a future paper optimized implementations and results on the breakdown of invariant tori.

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This paper shows how one of the developers of QWERTY continued to use the trade secret that underlay its development to seek further efficiency improvements after its introduction. It provides further evidence that this was the principle used to design QWERTY in the first place and adds further weight to arguments that QWERTY itself was a consequence of creative design and an integral part of a highly efficient system rather than an accident of history. This further serves to raise questions over QWERTY's forced servitude as 'paradigm case' of inferior standard in the path dependence literature. The paper also shows how complementarities in forms of intellectual property rights protection played integral roles in the development of QWERTY and the search for improvements on it, and also helped effectively conceal the source of the efficiency advantages that QWERTY helped deliver.

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We consider a frictional two-sided matching market in which one side uses public cheap talk announcements so as to attract the other side. We show that if the first-price auction is adopted as the trading protocol, then cheap talk can be perfectly informative, and the resulting market outcome is efficient, constrained only by search frictions. We also show that the performance of an alternative trading protocol in the cheap-talk environment depends on the level of price dispersion generated by the protocol: If a trading protocol compresses (spreads) the distribution of prices relative to the first-price auction, then an efficient fully revealing equilibrium always (never) exists. Our results identify the settings in which cheap talk can serve as an efficient competitive instrument, in the sense that the central insights from the literature on competing auctions and competitive search continue to hold unaltered even without ex ante price commitment.

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In a market in which sellers compete by posting mechanisms, we study how the properties of the meeting technology affect the mechanism that sellers select. In general, sellers have incentive to use mechanisms that are socially efficient. In our environment, sellers achieve this by posting an auction with a reserve price equal to their own valuation, along with a transfer that is paid by (or to) all buyers with whom the seller meets. However, we define a novel condition on meeting technologies, which we call “invariance,” and show that the transfer is equal to zero if and only if the meeting technology satisfies this condition.

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We develop a life-cycle model of the labor market in which different worker-firm matches have different quality and the assignment of the right workers to the right firms is time consuming because of search and learning frictions. The rate at which workers move between unemployment, employment and across different firms is endogenous because search is directed and, hence, workers can choose whether to seek low-wage jobs that are easy to find or high-wage jobs that are hard to find. We calibrate our theory using data on labor market transitions aggregated across workers of different ages. We validate our theory by showing that it predicts quite well the pattern of labor market transitions for workers of different ages. Finally, we use our theory to decompose the age profiles of transition rates, wages and productivity into the effects of age variation in work-life expectancy, human capital and match quality.

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This paper evaluates the effects of policy interventions on sectoral labour markets and the aggregate economy in a business cycle model with search and matching frictions. We extend the canonical model by including capital-skill complementarity in production, labour markets with skilled and unskilled workers and on-the-job-learning (OJL) within and across skill types. We first find that, the model does a good job at matching the cyclical properties of sectoral employment and the wage-skill premium. We next find that vacancy subsidies for skilled and unskilled jobs lead to output multipliers which are greater than unity with OJL and less than unity without OJL. In contrast, the positive output effects from cutting skilled and unskilled income taxes are close to zero. Finally, we find that the sectoral and aggregate effects of vacancy subsidies do not depend on whether they are financed via public debt or distorting taxes.

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This paper examines the antecedents and innovation consequences of the methods firms adopt in organizing their search strategies. From a theoretical perspective, organizational search is described using a typology that shows how firms implement exploration and exploitation search activities that span their organizational boundaries. This typology includes three models of implementation: ambidextrous, specialized, and diversified implementation. From an empirical perspective, the paper examines the performance consequences when applying these models, and compares their capacity to produce complementarities. Additionally, since firms' choices in matters of organizational search are viewed as endogenous variables, the paper examines the drivers affecting them and identifies the importance of firms' absorptive capacity and diversified technological opportunities in determining these choices. The empirical design of the paper draws on new data for manufacturing firms in Spain, surveyed between 2003 and 2006.

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A rational method of search for natural neolignans of desired structures is outlined. This involves consultation of a collection of chemical profiles of plant families. The profiles are assembled considering the biosynthetic class (in the present case lignoids), subclass (neolignans), structural types (neolignan skeleta) and relative frequency of substitutional derivatives belonging to each type (known compounds). The method is of course applicable to ani class of natural products. Its use in the case of neolignans is here selected as an exemple in view of the recently discovered antagonism towards PAF of kadsurenone, a representative of this subclass of phytochemicals. Application of the chemical profiles to phylogenetic studies is illustrated.

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A systematic search for solasodine, an important staring material for the partial synthesis of steroidal hormones as well as other potentially bioactive constituents of various Solanum species of Brazil has been undertaken. Thus, the fruits of S. paludosum, S. asperum, S. sessiliforum and Solanum sp. were found to contain significant amounts of solasodine. The root bark of S. paludosum which showe durare like activity yelded tomatidenol and another yet unidentified alkaloid responsible for the biological activity. The fruits of S. asperum yelded a new spirosolane alkaloid, solaparnaine. The stem bark of S. pseudo-quina showed convulsive and exitatory activity from which (25S)-isosolafloridine was identified as the active principle. In addition, the latter alkaloid was also found to show antimicrobial activity.

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Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

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