32 resultados para Goal programming

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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This contribution compares existing and newly developed techniques for geometrically representing mean-variances-kewness portfolio frontiers based on the rather widely adapted methodology of polynomial goal programming (PGP) on the one hand and the more recent approach based on the shortage function on the other hand. Moreover, we explain the working of these different methodologies in detail and provide graphical illustrations. Inspired by these illustrations, we prove a generalization of the well-known two fund separation theorem from traditionalmean-variance portfolio theory.

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Informe de investigación realizado a partir de una estancia en el Department of Computer and Information Science de la Norwegian University of Science and Technology (NTNU), Noruega, entre setiembre i diciembre de 2006. El uso de componentes de software llamados Commercial-Off-The-Shelf (COTS) en el desarrollo de sistemas basados en componentes implica varios retos. Uno de ellos es la falta de información disponible y adecuada para dar soporte al proceso de selección de componentes a ser integrados. Para lidiar con estos problemas, se esta desarrollando un trabajo de tesis que propone un método llamado GOThIC (Goal-Oriented Taxonomy and reuse Infrastructure Construction). El método está orientado a construir una infrastructura de reuse para facilitar la búsqueda y reuse de componentes COTS. La estancia en la NTNU, reportada en este documento, tuvo como objetivo primordial las mejora del método y la obtención de datos empíricos para darle soporte. Algunos de los principales resultados fueron la obtención de datos empíricos fundamentando la utilización del método en ámbitos industriales de selección de componentes COTS, así como una nueva estrategia para conseguir de forma factible e incremental, la federación y reuso de los diferentes esfuerzos existentes para encontrar, seleccionar y mantener componentes COTS y Open Source (OSS) -comúnmente llamados componentes Off-The-Shelf (OTS) - en forma estructurada.

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En aquest projecte s’ha estudiat el disseny d’una plataforma robòtica mòbil per un PBL (Aprenentatge Basat en Problemes) en enginyeria informàtica. El principal objectiu és introduir aquest model en l’ensenyament universitari, com a complement de diferents assignatures de primer curs. Per arribar a aconseguir aquests objectius, s’ha dissenyat i construït una plataforma robòtica, dirigida per un microcontrolador i dotada de diversos sensors per interactuar amb l’entorn. El robot permet diferents tipus de programació i esta especialment dissenyada per ser una bona experiència educativa.

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L'objectiu principal d'aquest projecte és ampliar la llibreria BinaryCodes, iniciada al 2007, que ens permet construir i manipular codis binaris lineals i no lineals. Per aquest motiu, s'han desenvolupat una sèrie de funcions, amb els seus corresponents tests i exemples, en l'entorn de programació matemàtica Magma. Aquestes funcions consisteixen bàsicament en la construcció de nous codis a partir d'altres ja existents.

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Avui en dia la biologia aporta grans quantitats de dades que només la informàtica pot tractar. Les aplicacions bioinformàtiques són la més important eina d’anàlisi i comparació que tenim per entendre la vida i aconseguir desxifrar aquestes dades. Aquest projecte centra el seu esforç en l’estudi de les aplicacions dedicades a l’alineament de seqüències genètiques, i més concretament a dos algoritmes, basats en programació dinàmica i òptims: el Needleman&Wunsch i el Smith&Waterman. Amb l’objectiu de millorar el rendiment d’aquests algoritmes per a alineaments de seqüències grans, proposem diferents versions d’implementació. Busquem millorar rendiments en temps i espai. Per a aconseguir millorar els resultats aprofitem el paral·lelisme. Els resultats dels anàlisis de les versions els comparem per obtenir les dades necessàries per valorar cost, guany i rendiment.

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L'objectiu és una aplicació que permeti realitzar el càlcul del volum de terres disponibles en el subsòl d'un àrea seleccionada. L'objectiu final del projecte serà crear un Sistema d'Informació Geogràfica SIG que ajudi a valorar quines parcel¿les de l'àrea seleccionada són les que disposen de més volum de terres per iniciar la seva explotació. Per a això, es disposa del programari gvSIG i les seves extensions (SEXTANTE) i de tota la informació que es pugui obtenir sobre els SIG, Cartografia, Geodèsia... Per dur a terme aquest projecte es necessita tenir experiència en Bases de dades, Programació Orientada a Objectes i seria recomanable tenir coneixements sobre Enginyeria del Programador. El projecte se centrarà en la utilització de gvSIG, com un exemple concret de programari SIG de lliure accés, solució desenvolupada per la ¿Conselleria d%o2019Obris Publiquis de la Generalitat Valenciana¿. Una part d'aquest projecte consistirà a avaluar aquest programari. El resultat final serà l'obtenció dels coneixements necessaris per poder treballar amb dades espacials a més d'una aplicació SIG per al càlcul del volum de terres d'un àrea seleccionada.

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El Treball Fi de Carrera (TFC) engloba l'anàlisi, el disseny i la implementació d'una aplicació web utilitzant la tecnologia Java y l'arquitectura J2EE. Com a primera tasca s'afegeix una planificació prèvia i també una memòria i presentació finals. El Treball consisteix en el desenvolupament de Globalteca, una aplicació que permet portar a terme la gestió de col·leccions a nivell personal com ara pel·lícules, llibres i música, i obert a altres usuaris que vulguin accedir-hi. L'objectiu és tenir tota la informació de les diferents col·leccions centralitzada.

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In This work we present a Web-based tool developed with the aim of reinforcing teaching and learning of introductory programming courses. This tool provides support for teaching and learning. From the teacher's perspective the system introduces important gains with respect to the classical teaching methodology. It reinforces lecture and laboratory sessions, makes it possible to give personalized attention to the student, assesses the degree of participation of the students and most importantly, performs a continuous assessment of the student's progress. From the student's perspective it provides a learning framework, consisting in a help environment and a correction environment, which facilitates their personal work. With this tool students are more motivated to do programming

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Large projects evaluation rises well known difficulties because -by definition- they modify the current price system; their public evaluation presents additional difficulties because they modify too existing shadow prices without the project. This paper analyzes -first- the basic methodologies applied until late 80s., based on the integration of projects in optimization models or, alternatively, based on iterative procedures with information exchange between two organizational levels. New methodologies applied afterwards are based on variational inequalities, bilevel programming and linear or nonlinear complementarity. Their foundations and different applications related with project evaluation are explored. As a matter of fact, these new tools are closely related among them and can treat more complex cases involving -for example- the reaction of agents to policies or the existence of multiple agents in an environment characterized by common functions representing demands or constraints on polluting emissions.

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Business processes designers take into account the resources that the processes would need, but, due to the variable cost of certain parameters (like energy) or other circumstances, this scheduling must be done when business process enactment. In this report we formalize the energy aware resource cost, including time and usage dependent rates. We also present a constraint programming approach and an auction-based approach to solve the mentioned problem including a comparison of them and a comparison of the proposed algorithms for solving them

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In a number of programs for gene structure prediction in higher eukaryotic genomic sequences, exon prediction is decoupled from gene assembly: a large pool of candidate exons is predicted and scored from features located in the query DNA sequence, and candidate genes are assembled from such a pool as sequences of nonoverlapping frame-compatible exons. Genes are scored as a function of the scores of the assembled exons, and the highest scoring candidate gene is assumed to be the most likely gene encoded by the query DNA sequence. Considering additive gene scoring functions, currently available algorithms to determine such a highest scoring candidate gene run in time proportional to the square of the number of predicted exons. Here, we present an algorithm whose running time grows only linearly with the size of the set of predicted exons. Polynomial algorithms rely on the fact that, while scanning the set of predicted exons, the highest scoring gene ending in a given exon can be obtained by appending the exon to the highest scoring among the highest scoring genes ending at each compatible preceding exon. The algorithm here relies on the simple fact that such highest scoring gene can be stored and updated. This requires scanning the set of predicted exons simultaneously by increasing acceptor and donor position. On the other hand, the algorithm described here does not assume an underlying gene structure model. Indeed, the definition of valid gene structures is externally defined in the so-called Gene Model. The Gene Model specifies simply which gene features are allowed immediately upstream which other gene features in valid gene structures. This allows for great flexibility in formulating the gene identification problem. In particular it allows for multiple-gene two-strand predictions and for considering gene features other than coding exons (such as promoter elements) in valid gene structures.

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Plan recognition is the problem of inferring the goals and plans of an agent from partial observations of her behavior. Recently, it has been shown that the problem can be formulated and solved usingplanners, reducing plan recognition to plan generation.In this work, we extend this model-basedapproach to plan recognition to the POMDP setting, where actions are stochastic and states are partially observable. The task is to infer a probability distribution over the possible goals of an agent whose behavior results from a POMDP model. The POMDP model is shared between agent and observer except for the true goal of the agent that is hidden to the observer. The observations are action sequences O that may contain gaps as some or even most of the actions done by the agent may not be observed. We show that the posterior goal distribution P(GjO) can be computed from the value function VG(b) over beliefs b generated by the POMDPplanner for each possible goal G. Some extensionsof the basic framework are discussed, and a numberof experiments are reported.

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Models incorporating more realistic models of customer behavior, as customers choosing froman offer set, have recently become popular in assortment optimization and revenue management.The dynamic program for these models is intractable and approximated by a deterministiclinear program called the CDLP which has an exponential number of columns. However, whenthe segment consideration sets overlap, the CDLP is difficult to solve. Column generationhas been proposed but finding an entering column has been shown to be NP-hard. In thispaper we propose a new approach called SDCP to solving CDLP based on segments and theirconsideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound onthe dynamic program but coincides with CDLP for the case of non-overlapping segments. Ifthe number of elements in a consideration set for a segment is not very large (SDCP) can beapplied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by(i) simulations, called the randomized concave programming (RCP) method, and (ii) by addingcuts to a recent compact formulation of the problem for a latent multinomial-choice model ofdemand (SBLP+). This latter approach turns out to be very effective, essentially obtainingCDLP value, and excellent revenue performance in simulations, even for overlapping segments.By formulating the problem as a separation problem, we give insight into why CDLP is easyfor the MNL with non-overlapping considerations sets and why generalizations of MNL posedifficulties. We perform numerical simulations to determine the revenue performance of all themethods on reference data sets in the literature.

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The choice network revenue management model incorporates customer purchase behavioras a function of the offered products, and is the appropriate model for airline and hotel networkrevenue management, dynamic sales of bundles, and dynamic assortment optimization.The optimization problem is a stochastic dynamic program and is intractable. A certainty-equivalencerelaxation of the dynamic program, called the choice deterministic linear program(CDLP) is usually used to generate dyamic controls. Recently, a compact linear programmingformulation of this linear program was given for the multi-segment multinomial-logit (MNL)model of customer choice with non-overlapping consideration sets. Our objective is to obtaina tighter bound than this formulation while retaining the appealing properties of a compactlinear programming representation. To this end, it is natural to consider the affine relaxationof the dynamic program. We first show that the affine relaxation is NP-complete even for asingle-segment MNL model. Nevertheless, by analyzing the affine relaxation we derive a newcompact linear program that approximates the dynamic programming value function betterthan CDLP, provably between the CDLP value and the affine relaxation, and often comingclose to the latter in our numerical experiments. When the segment consideration sets overlap,we show that some strong equalities called product cuts developed for the CDLP remain validfor our new formulation. Finally we perform extensive numerical comparisons on the variousbounds to evaluate their performance.

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We present a new unifying framework for investigating throughput-WIP(Work-in-Process) optimal control problems in queueing systems,based on reformulating them as linear programming (LP) problems withspecial structure: We show that if a throughput-WIP performance pairin a stochastic system satisfies the Threshold Property we introducein this paper, then we can reformulate the problem of optimizing alinear objective of throughput-WIP performance as a (semi-infinite)LP problem over a polygon with special structure (a thresholdpolygon). The strong structural properties of such polygones explainthe optimality of threshold policies for optimizing linearperformance objectives: their vertices correspond to the performancepairs of threshold policies. We analyze in this framework theversatile input-output queueing intensity control model introduced byChen and Yao (1990), obtaining a variety of new results, including (a)an exact reformulation of the control problem as an LP problem over athreshold polygon; (b) an analytical characterization of the Min WIPfunction (giving the minimum WIP level required to attain a targetthroughput level); (c) an LP Value Decomposition Theorem that relatesthe objective value under an arbitrary policy with that of a giventhreshold policy (thus revealing the LP interpretation of Chen andYao's optimality conditions); (d) diminishing returns and invarianceproperties of throughput-WIP performance, which underlie thresholdoptimality; (e) a unified treatment of the time-discounted andtime-average cases.