933 resultados para Goal Programming


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In the field of perinatality, development of prenatal diagnosis and neonatal management have been impressive. But these were also associated with the emergence of the increasingly important emotional dimension for parents and professionals. Obstetricians dealing with the difficult breaking of bad news, the uncertainties of prenatal diagnosis and the complex somatic, psychological and social follow-up have to work in a multidisciplinary approach. The securing role of a coherent teamwork is recognised by parents as well as health care providers This article discusses interprofessional relationship as an obstetrical goal and give some landmarks in order to improve the management and the collaboration with parents.

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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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The hypocretins (Hcrts), also called orexins, are two neuropeptides secreted by a few thousand neurons restricted to the lateral hypothalamus. The Hcrt peptides bind to two receptors located in nuclei associated with diverse cognitive and physiological functions. Experimental evidence has demonstrated that the physiological roles of hypocretins extend far beyond its initial role in food consumption and has emerged as a key system in the fields of sleep disorders and drug addiction. Here, we discuss recent evidence demonstrating a key role of hypocretin in the motivation for reward seeking in general, and drug taking in particular, and we delineate a physiological framework for this peptidergic system in orchestrating the appropriate levels of alertness required for the elaboration and the execution of goal-oriented behaviors. We propose a general role for hypocretins in mediating arousal, especially when an organism must respond to unexpected stressors and environmental challenges, which serve to shape survival behaviors. We also discuss the limit of the current experimental paradigms to address the question of how a system normally involved in the regulation of vigilance states and hyperarousal may promote a pathological state that elicits compulsive craving and relapse to drug seeking.

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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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Therapeutic goal of vitamin D: optimal serum level and dose requirements Results of randomized controlled trials and meta-analyses investigating the effect of vitamin D supplementation on falls and fractures are inconsistent. The optimal serum level 25(OH) vitamin D for musculoskeletal and global health is > or = 30 ng/ml (75 nmol/l) for some experts and 20 ng/ml (50 nmol/l) for some others. A daily dose of vitamin D is better than high intermittent doses to reach this goal. High dose once-yearly vitamin D therapy may increase the incidence of fractures and falls. High serum level of vitamin D is probably harmful for the musculoskeletal system and health at large. The optimal benefits for musculoskeletal health are obtained with an 800 UI daily dose and a serum level of near 30 ng/ml (75 nmol/l).

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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.

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This paper introduces the approach of using Total Unduplicated Reach and Frequency analysis (TURF) to design a product line through a binary linear programming model. This improves the efficiency of the search for the solution to the problem compared to the algorithms that have been used to date. The results obtained through our exact algorithm are presented, and this method shows to be extremely efficient both in obtaining optimal solutions and in computing time for very large instances of the problem at hand. Furthermore, the proposed technique enables the model to be improved in order to overcome the main drawbacks presented by TURF analysis in practice.

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The Iowa Transportation Improvement Program (Program) is published to inform Iowans of planned investments in our state's transportation system. The Iowa Transportation Commission (Commission) and Iowa Department of Transportation (Iowa DOT) are committed to programming those investments in a fiscally responsible manner. Iowa's transportation system is multi-modal; therefore, the Program encompasses investments in aviation, transit, railroads, trails, and highways. A major component of the Program is the highway section. The FY2009-2013 highway section is financially balanced and was developed to achieve several objectives. The Commission's primary highway investment objective is the safety, maintenance and preservation of Iowa's existing highway system. The Commission has allocated an annual average of $321 million to achieve this objective. This includes $185 million in 2009 and $170 million annually in years 2010-2013 for preserving the interstate system. It includes $114 million in 2009, $100 million in 2010 and $90 million annually in years 2011-2013 for non-interstate pavement preservation. It includes $38 million annually in 2009 and 2010, and $35 million annually in years 2011-2013 for non-interstate bridges. In addition, $15 million annually is allocated for safety projects. However, due to increasing construction costs, flattened revenues and overall highway systems needs, the Commission acknowledges that insufficient funds are being invested in the maintenance and preservation of the existing highway system. Another objective involves investing in projects that have received funding from the federal transportation act and/or subsequent federal transportation appropriation acts. In particular, funding is being used where it will complete a project, corridor or useable segment of a larger project. As an investment goal, the Commission also wishes to advance highway projects that address the state's highway capacity and economic development needs. Projects that address these needs and were included for completion in the previous program have been advanced into this year's Program to maintain their scheduled completion. This program also includes a small number of other projects that generally either represent a final phase of a partially programmed project or an additional segment of a partially completed corridor. The TIME-21 bill, Senate File 2420, signed by Governor Chet Culver on April 22, provides additional funding to cities, counties and the Iowa DOT for road improvements. This will result in additional revenue to the Primary Road Fund beginning in the second half of FY2009 and gradually increase over time. The additional funding will be included in future highway programming objectives and proposals and is not reflected in this highway program. The Iowa DOT and Commission appreciate the public's involvement in the state's transportation planning process. Comments received personally, by letter, or through participation in the Commission's regular meetings or public input meetings held around the state each year are invaluable in providing guidance for the future of Iowa's transportation system. It should be noted that this document is a planning guide. It does not represent a binding commitment or obligation of the Commission or Iowa DOT, and is subject to change. You are invited to visit the Iowa DOT's Web site at iowadot.gov for additional and regular updates about the department's programs and activities.