909 resultados para ALLOCATION


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Project Management involves onetime endeavors that demand for getting it right the first time. On the other hand, project scheduling, being one of the most modeled project management process stages, still faces a wide gap from theory to practice. Demanding computational models and their consequent call for simplification, divert the implementation of such models in project management tools from the actual day to day project management process. Special focus is being made to the robustness of the generated project schedules facing the omnipresence of uncertainty. An "easy" way out is to add, more or less cleverly calculated, time buffers that always result in project duration increase and correspondingly, in cost. A better approach to deal with uncertainty seems to be to explore slack that might be present in a given project schedule, a fortiori when a non-optimal schedule is used. The combination of such approach to recent advances in modeling resource allocation and scheduling techniques to cope with the increasing flexibility in resources, as can be expressed in "Flexible Resource Constraint Project Scheduling Problem" (FRCPSP) formulations, should be a promising line of research to generate more adequate project management tools. In reality, this approach has been frequently used, by project managers in an ad-hoc way.

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The authors propose a mathematical model to minimize the project total cost where there are multiple resources constrained by maximum availability. They assume the resources as renewable and the activities can use any subset of resources requiring any quantity from a limited real interval. The stochastic nature is inferred by means of a stochastic work content defined per resource within an activity and following a known distribution and the total cost is the sum of the resource allocation cost with the tardiness cost or earliness bonus in case the project finishes after or before the due date, respectively. The model was computationally implemented relying upon an interchange of two global optimization metaheuristics – the electromagnetism-like mechanism and the evolutionary strategies. Two experiments were conducted testing the implementation to projects with single and multiple resources, and with or without maximum availability constraints. The set of collected results shows good behavior in general and provide a tool to further assist project manager decision making in the planning phase.

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Published online first in 10 July 2013

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Density-dependent responses are an important component of the organism life-history, and the resource allocation theory is a central concept to the life-history theory. When resource allocation varies due to environmental changes, a plant may change its morphology or physiology to cope with the new conditions, a process known as phenotypic plasticity. Our study aimed to evaluate how plant density affects Eichhornia crassipes allocation patterns. A total of 214 individuals in high and low density were collected. The density effect was observed in all plant traits examined including biomass accumulation. All traits of E. crassipes demonstrated higher values in high density conditions, except for biomass of leaves. Density exhibited a high influence on vegetative traits of E. crassipes, but did not influence allocation pattern, since a trade-off among the vegetative traits was not found. The morphological plasticity and the absence of trade-offs were discussed as strategies to overcome neighbor plants in competition situations. In high density conditions, there were clear changes in the morphology of the plants which probably allows for their survival in a highly competitive environment.

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Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

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Dissertação de mestrado integrado em Engenharia Civil

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Tese de Doutoramento em Engenharia Civil.

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Dissertação de mestrado integrado em Engenharia Civil

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Dissertação de mestrado em Estatística

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Background: Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results. Objective: To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it. Methods: The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals’ homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious. Results: The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals. Conclusion: The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate.

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I consider the problem of assigning agents to objects where each agent must pay the price of the object he gets and prices must sum to a given number. The objective is to select an assignment-price pair that is envy-free with respect to the true preferences. I prove that the proposed mechanism will implement both in Nash and strong Nash the set of envy-free allocations. The distinguishing feature of the mechanism is that it treats the announced preferences as the true ones and selects an envy-free allocation with respect to the announced preferences.

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In this note we study uncertainty sequencing situations, i.e., 1-machine sequencing situations in which no initial order is specified. We associate cooperative games with these sequencing situations, study their core, and provide links with the classic sequencing games introduced by Curiel et al. (1989). Moreover, we propose and characterize two simple cost allocation rules for uncertainty sequencing situations with equal processing times.

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We study situations of allocating positions or jobs to students or workers based on priorities. An example is the assignment of medical students to hospital residencies on the basis of one or several entrance exams. For markets without couples, e.g., for ``undergraduate student placement,'' acyclicity is a necessary and sufficient condition for the existence of a fair and efficient placement mechanism (Ergin, 2002). We show that in the presence of couples, which introduces complementarities into the students' preferences, acyclicity is still necessary, but not sufficient (Theorem 4.1). A second necessary condition (Theorem 4.2) is ``priority-togetherness'' of couples. A priority structure that satisfies both necessary conditions is called pt-acyclic. For student placement problems where all quotas are equal to one we characterize pt-acyclicity (Lemma 5.1) and show that it is a sufficient condition for the existence of a fair and efficient placement mechanism (Theorem 5.1). If in addition to pt-acyclicity we require ``reallocation-'' and ``vacancy-fairness'' for couples, the so-called dictator-bidictator placement mechanism is the unique fair and efficient placement mechanism (Theorem 5.2). Finally, for general student placement problems, we show that pt-acyclicity may not be sufficient for the existence of a fair and efficient placement mechanism (Examples 5.4, 5.5, and 5.6). We identify a sufficient condition such that the so-called sequential placement mechanism produces a fair and efficient allocation (Theorem 5.3).

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We propose a new solution concept to address the problem of sharing a surplus among the agents generating it. The sharing problem is formulated in the preferences-endowments space. The solution is defined in a recursive manner incorporating notions of consistency and fairness and relying on properties satisfied by the Shapley value for Transferable Utility (TU) games. We show a solution exists, and refer to it as an Ordinal Shapley value (OSV). The OSV associates with each problem an allocation as well as a matrix of concessions ``measuring'' the gains each agent foregoes in favor of the other agents. We analyze the structure of the concessions, and show they are unique and symmetric. Next we characterize the OSV using the notion of coalitional dividends, and furthermore show it is monotone in an agent's initial endowments and satisfies anonymity. Finally, similarly to the weighted Shapley value for TU games, we construct a weighted OSV as well.

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We consider the following allocation problem: A fixed number of public facilities must be located on a line. Society is composed of $N$ agents, who must be allocated to one and only one of these facilities. Agents have single peaked preferences over the possible location of the facilities they are assigned to, and do not care about the location of the rest of facilities. There is no congestion. In this context, we observe that if a public decision is a Condorcet winner, then it satisfies nice properties of internal and external stability. Though in many contexts and for some preference profiles there may be no Condorcet winners, we study the extent to which stability can be made compatible with the requirement of choosing Condorcet winners whenever they exist.