840 resultados para Optimal allocation
Resumo:
Two populations of the wasp Trypoxylon rogenhoferi Kohl, 1884 from São Carlos and Luís Antônio, State of São Paulo, Brazil, were observed and sampled from May 1999 to February 2001 using trap-nests. This mass-provisioning wasp was used to test some aspects of optimal sex allocation theory. Both populations fit all the predictions of the models of Green and Brockmann and Grafen. Maternal provisions determined the size of each offspring, and females allocated well-stocked brood cells to daughters, the sex that benefits most being large. This strategy resulted in a difference in size between the sexes. In São Carlos, female weight at emergence was 1.18 times that of males, in Luís Antônio this value was 1.13. The brood cell volume was correlated with both wing length and weight at emergence in both sexes, and the chance that a given brood cell contained a male offspring decreased with increased brood cell volume. In T. rogenhoferi female body size was related to fitness. Larger females were able to collect more mass of spiders per day, the spiders they captured were heavier, and they provisioned more brood cells per day. They also produced larger daughters. For males, no relationship between body size and fitness was found, but the data were scarce. Since the patterns of provisioning were variable among different females in both study sites, it is possible that the females not follow a unique strategy for sex allocation. The sex ratio and/or investment ratio in the São Carlos population was female-biased and in Luís Antônio, male-biased. In spite of the influence of trap-nests diameters on male production in Luís Antônio, there is some evidence that in São Carlos population the local availability of prey and/or lower rate of parasitism may be major forces in determining the observed sex ratio, but further studies are necessary to verify such hypothesis.
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We present a polyhedral framework for establishing general structural properties on optimal solutions of stochastic scheduling problems, where multiple job classes vie for service resources: the existence of an optimal priority policy in a given family, characterized by a greedoid(whose feasible class subsets may receive higher priority), where optimal priorities are determined by class-ranking indices, under restricted linear performance objectives (partial indexability). This framework extends that of Bertsimas and Niño-Mora (1996), which explained the optimality of priority-index policies under all linear objectives (general indexability). We show that, if performance measures satisfy partial conservation laws (with respect to the greedoid), which extend previous generalized conservation laws, then theproblem admits a strong LP relaxation over a so-called extended greedoid polytope, which has strong structural and algorithmic properties. We present an adaptive-greedy algorithm (which extends Klimov's) taking as input the linear objective coefficients, which (1) determines whether the optimal LP solution is achievable by a policy in the given family; and (2) if so, computes a set of class-ranking indices that characterize optimal priority policies in the family. In the special case of project scheduling, we show that, under additional conditions, the optimal indices can be computed separately for each project (index decomposition). We further apply the framework to the important restless bandit model (two-action Markov decision chains), obtaining new index policies, that extend Whittle's (1988), and simple sufficient conditions for their validity. These results highlight the power of polyhedral methods (the so-called achievable region approach) in dynamic and stochastic optimization.
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The earning structure in science is known to be flat relative to the one in theprivate sector, which could cause a brain drain toward the private sector. In thispaper, we assume that agents value both money and fame and study the role ofthe institution of science in the allocation of talent between the science sector andthe private sector. Following works on the Sociology of Science, we model theinstitution of science as a mechanism distributing fame (i.e. peer recognition). Weshow that since the intrinsic performance is less noisy signal of talent in the sciencesector than in the private sector, a good institution of science can mitigate thebrain drain. We also find that providing extra monetary incentives through themarket might undermine the incentives provided by the institution and therebyworsen the brain drain. Finally, we study the optimal balance between monetaryand non-monetary incentives in science.
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The goal of this paper is to present an optimal resource allocation model for the regional allocation of public service inputs. Theproposed solution leads to maximise the relative public service availability in regions located below the best availability frontier, subject to exogenous budget restrictions and equality ofaccess for equal need criteria (equity-based notion of regional needs). The construction of non-parametric deficit indicators is proposed for public service availability by a novel application of Data Envelopment Analysis (DEA) models, whose results offer advantages for the evaluation and improvement of decentralised public resource allocation systems. The method introduced in this paper has relevance as a resource allocation guide for the majority of services centrally funded by the public sector in a given country, such as health care, basic and higher education, citizen safety, justice, transportation, environmental protection, leisure, culture, housing and city planning, etc.
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Like many organisms, the cladoceran Simocephalus vetulus (Müller) continues to grow when reproducing, whereas the optimal strategy is to stop growing at maturity, and to invest all available production into reproduction thereafter. It has been proposed that a size constraint is responsible for the observed strategy (Perrin, Ruedi & Saiah, 1987), by preventing organisms from investing more than a given amount of energy into reproduction. This hypothesis is developed here and the two folowing prediction are derived: (1) the onset of reproduction should be independent of age and (2) the reproductive investement should be size-specific, thus independent of the productin rate. Both predictions are tested by rearing a clone of S.vetulus in a gradient of productivity. The results support the first prediction, but not the second one, so that the size-constraint hypothesis is disproved.
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BACKGROUND AND OBJECTIVES: The SBP values to be achieved by antihypertensive therapy in order to maximize reduction of cardiovascular outcomes are unknown; neither is it clear whether in patients with a previous cardiovascular event, the optimal values are lower than in the low-to-moderate risk hypertensive patients, or a more cautious blood pressure (BP) reduction should be obtained. Because of the uncertainty whether 'the lower the better' or the 'J-curve' hypothesis is correct, the European Society of Hypertension and the Chinese Hypertension League have promoted a randomized trial comparing antihypertensive treatment strategies aiming at three different SBP targets in hypertensive patients with a recent stroke or transient ischaemic attack. As the optimal level of low-density lipoprotein cholesterol (LDL-C) level is also unknown in these patients, LDL-C-lowering has been included in the design. PROTOCOL DESIGN: The European Society of Hypertension-Chinese Hypertension League Stroke in Hypertension Optimal Treatment trial is a prospective multinational, randomized trial with a 3 × 2 factorial design comparing: three different SBP targets (1, <145-135; 2, <135-125; 3, <125 mmHg); two different LDL-C targets (target A, 2.8-1.8; target B, <1.8 mmol/l). The trial is to be conducted on 7500 patients aged at least 65 years (2500 in Europe, 5000 in China) with hypertension and a stroke or transient ischaemic attack 1-6 months before randomization. Antihypertensive and statin treatments will be initiated or modified using suitable registered agents chosen by the investigators, in order to maintain patients within the randomized SBP and LDL-C windows. All patients will be followed up every 3 months for BP and every 6 months for LDL-C. Ambulatory BP will be measured yearly. OUTCOMES: Primary outcome is time to stroke (fatal and non-fatal). Important secondary outcomes are: time to first major cardiovascular event; cognitive decline (Montreal Cognitive Assessment) and dementia. All major outcomes will be adjudicated by committees blind to randomized allocation. A Data and Safety Monitoring Board has open access to data and can recommend trial interruption for safety. SAMPLE SIZE CALCULATION: It has been calculated that 925 patients would reach the primary outcome after a mean 4-year follow-up, and this should provide at least 80% power to detect a 25% stroke difference between SBP targets and a 20% difference between LDL-C targets.
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Que ce soit d'un point de vue, urbanistique, social, ou encore de la gouvernance, l'évolution des villes est un défi majeur de nos sociétés contemporaines. En offrant la possibilité d'analyser des configurations spatiales et sociales existantes ou en tentant de simuler celles à venir, les systèmes d'information géographique sont devenus incontournables dans la gestion et dans la planification urbaine. En cinq ans la population de la ville de Lausanne est passée de 134'700 à 140'570 habitants, alors que les effectifs de l'école publique ont crû de 12'200 à 13'500 élèves. Cet accroissement démographique associé à un vaste processus d'harmonisation de la scolarité obligatoire en Suisse ont amené le Service des écoles à mettre en place et à développer en collaboration avec l'université de Lausanne des solutions SIG à même de répondre à différentes problématiques spatiales. Établies en 1989, les limites des établissements scolaires (bassins de recrutement) ont dû être redéfinies afin de les réadapter aux réalités d'un paysage urbain et politique en pleine mutation. Dans un contexte de mobilité et de durabilité, un système d'attribution de subventions pour les transports publics basé sur la distance domicile-école et sur l'âge des écoliers, a été conçu. La réalisation de ces projets a nécessité la construction de bases de données géographiques ainsi que l'élaboration de nouvelles méthodes d'analyses exposées dans ce travail. Cette thèse s'est ainsi faite selon une dialectique permanente entre recherches théoriques et nécessités pratiques. La première partie de ce travail porte sur l'analyse du réseau piéton de la ville. La morphologie du réseau est investiguée au travers d'approches multi-échelles du concept de centralité. La première conception, nommée sinuo-centralité ("straightness centrality"), stipule qu'être central c'est être relié aux autres en ligne droite. La deuxième, sans doute plus intuitive, est intitulée centricité ("closeness centrality") et exprime le fait qu'être central c'est être proche des autres (fig. 1, II). Les méthodes développées ont pour but d'évaluer la connectivité et la marchabilité du réseau, tout en suggérant de possibles améliorations (création de raccourcis piétons). Le troisième et dernier volet théorique expose et développe un algorithme de transport optimal régularisé. En minimisant la distance domicile-école et en respectant la taille des écoles, l'algorithme permet de réaliser des scénarios d'enclassement. L'implémentation des multiplicateurs de Lagrange offre une visualisation du "coût spatial" des infrastructures scolaires et des lieux de résidence des écoliers. La deuxième partie de cette thèse retrace les aspects principaux de trois projets réalisés dans le cadre de la gestion scolaire. À savoir : la conception d'un système d'attribution de subventions pour les transports publics, la redéfinition de la carte scolaire, ou encore la simulation des flux d'élèves se rendant à l'école à pied. *** May it be from an urbanistic, a social or from a governance point of view, the evolution of cities is a major challenge in our contemporary societies. By giving the opportunity to analyse spatial and social configurations or attempting to simulate future ones, geographic information systems cannot be overlooked in urban planning and management. In five years, the population of the city of Lausanne has grown from 134'700 to 140'570 inhabitants while the numbers in public schools have increased from 12'200 to 13'500 students. Associated to a considerable harmonisation process of compulsory schooling in Switzerland, this demographic rise has driven schooling services, in collaboration with the University of Lausanne, to set up and develop GIS capable of tackling various spatial issues. Established in 1989, the school districts had to be altered so that they might fit the reality of a continuously changing urban and political landscape. In a context of mobility and durability, an attribution system for public transport subventions based on the distance between residence and school and on the age of the students was designed. The implementation of these projects required the built of geographical databases as well as the elaboration of new analysis methods exposed in this thesis. The first part of this work focuses on the analysis of the city's pedestrian network. Its morphology is investigated through multi-scale approaches of the concept of centrality. The first conception, named the straightness centrality, stipulates that being central is being connected to the others in a straight line. The second, undoubtedly more intuitive, is called closeness centrality and expresses the fact that being central is being close to the others. The goal of the methods developed is to evaluate the connectivity and walkability of the network along with suggesting possible improvements (creation of pedestrian shortcuts).The third and final theoretical section exposes and develops an algorithm of regularised optimal transport. By minimising home to school distances and by respecting school capacity, the algorithm enables the production of student allocation scheme. The implementation of the Lagrange multipliers offers a visualisation of the spatial cost associated to the schooling infrastructures and to the student home locations. The second part of this thesis recounts the principal aspects of three projects fulfilled in the context of school management. It focuses namely on the built of an attribution system for public transport subventions, a school redistricting process and on simulating student pedestrian flows.
Resumo:
Dans cette thèse, nous étudions quelques problèmes fondamentaux en mathématiques financières et actuarielles, ainsi que leurs applications. Cette thèse est constituée de trois contributions portant principalement sur la théorie de la mesure de risques, le problème de l’allocation du capital et la théorie des fluctuations. Dans le chapitre 2, nous construisons de nouvelles mesures de risque cohérentes et étudions l’allocation de capital dans le cadre de la théorie des risques collectifs. Pour ce faire, nous introduisons la famille des "mesures de risque entropique cumulatifs" (Cumulative Entropic Risk Measures). Le chapitre 3 étudie le problème du portefeuille optimal pour le Entropic Value at Risk dans le cas où les rendements sont modélisés par un processus de diffusion à sauts (Jump-Diffusion). Dans le chapitre 4, nous généralisons la notion de "statistiques naturelles de risque" (natural risk statistics) au cadre multivarié. Cette extension non-triviale produit des mesures de risque multivariées construites à partir des données financiéres et de données d’assurance. Le chapitre 5 introduit les concepts de "drawdown" et de la "vitesse d’épuisement" (speed of depletion) dans la théorie de la ruine. Nous étudions ces concepts pour des modeles de risque décrits par une famille de processus de Lévy spectrallement négatifs.
Optimal Methodology for Synchronized Scheduling of Parallel Station Assembly with Air Transportation
Resumo:
We present an optimal methodology for synchronized scheduling of production assembly with air transportation to achieve accurate delivery with minimized cost in consumer electronics supply chain (CESC). This problem was motivated by a major PC manufacturer in consumer electronics industry, where it is required to schedule the delivery requirements to meet the customer needs in different parts of South East Asia. The overall problem is decomposed into two sub-problems which consist of an air transportation allocation problem and an assembly scheduling problem. The air transportation allocation problem is formulated as a Linear Programming Problem with earliness tardiness penalties for job orders. For the assembly scheduling problem, it is basically required to sequence the job orders on the assembly stations to minimize their waiting times before they are shipped by flights to their destinations. Hence the second sub-problem is modelled as a scheduling problem with earliness penalties. The earliness penalties are assumed to be independent of the job orders.
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Dynamic optimization methods have become increasingly important over the last years in economics. Within the dynamic optimization techniques employed, optimal control has emerged as the most powerful tool for the theoretical economic analysis. However, there is the need to advance further and take account that many dynamic economic processes are, in addition, dependent on some other parameter different than time. One can think of relaxing the assumption of a representative (homogeneous) agent in macro- and micro-economic applications allowing for heterogeneity among the agents. For instance, the optimal adaptation and diffusion of a new technology over time, may depend on the age of the person that adopted the new technology. Therefore, the economic models must take account of heterogeneity conditions within the dynamic framework. This thesis intends to accomplish two goals. The first goal is to analyze and revise existing environmental policies that focus on defining the optimal management of natural resources over time, by taking account of the heterogeneity of environmental conditions. Thus, the thesis makes a policy orientated contribution in the field of environmental policy by defining the necessary changes to transform an environmental policy based on the assumption of homogeneity into an environmental policy which takes account of heterogeneity. As a result the newly defined environmental policy will be more efficient and likely also politically more acceptable since it is tailored more specifically to the heterogeneous environmental conditions. Additionally to its policy orientated contribution, this thesis aims making a methodological contribution by applying a new optimization technique for solving problems where the control variables depend on two or more arguments --- the so-called two-stage solution approach ---, and by applying a numerical method --- the Escalator Boxcar Train Method --- for solving distributed optimal control problems, i.e., problems where the state variables, in addition to the control variables, depend on two or more arguments. Chapter 2 presents a theoretical framework to determine optimal resource allocation over time for the production of a good by heterogeneous producers, who generate a stock externalit and derives government policies to modify the behavior of competitive producers in order to achieve optimality. Chapter 3 illustrates the method in a more specific context, and integrates the aspects of quality and time, presenting a theoretical model that allows to determine the socially optimal outcome over time and space for the problem of waterlogging in irrigated agricultural production. Chapter 4 of this thesis concentrates on forestry resources and analyses the optimal selective-logging regime of a size-distributed forest.
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A novel Swarm Intelligence method for best-fit search, Stochastic Diffusion Search, is presented capable of rapid location of the optimal solution in the search space. Population based search mechanisms employed by Swarm Intelligence methods can suffer lack of convergence resulting in ill defined stopping criteria and loss of the best solution. Conversely, as a result of its resource allocation mechanism, the solutions SDS discovers enjoy excellent stability.
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Practical applications of portfolio optimisation tend to proceed on a “top down” basis where funds are allocated first at asset class level (between, say, bonds, cash, equities and real estate) and then, progressively, at sub-class level (within property to sectors, office, retail, industrial for example). While there are organisational benefits from such an approach, it can potentially lead to sub-optimal allocations when compared to a “global” or “side-by-side” optimisation. This will occur where there are correlations between sub-classes across the asset divide that are masked in aggregation – between, for instance, City offices and the performance of financial services stocks. This paper explores such sub-class linkages using UK monthly stock and property data. Exploratory analysis using clustering procedures and factor analysis suggests that property performance and equity performance are distinctive: there is little persuasive evidence of contemporaneous or lagged sub-class linkages. Formal tests of the equivalence of optimised portfolios using top-down and global approaches failed to demonstrate significant differences, whether or not allocations were constrained. While the results may be a function of measurement of market returns, it is those returns that are used to assess fund performance. Accordingly, the treatment of real estate as a distinct asset class with diversification potential seems justified.
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We study a two-way relay network (TWRN), where distributed space-time codes are constructed across multiple relay terminals in an amplify-and-forward mode. Each relay transmits a scaled linear combination of its received symbols and their conjugates,with the scaling factor chosen based on automatic gain control. We consider equal power allocation (EPA) across the relays, as well as the optimal power allocation (OPA) strategy given access to instantaneous channel state information (CSI). For EPA, we derive an upper bound on the pairwise-error-probability (PEP), from which we prove that full diversity is achieved in TWRNs. This result is in contrast to one-way relay networks, in which case a maximum diversity order of only unity can be obtained. When instantaneous CSI is available at the relays, we show that the OPA which minimizes the conditional PEP of the worse link can be cast as a generalized linear fractional program, which can be solved efficiently using the Dinkelback-type procedure.We also prove that, if the sum-power of the relay terminals is constrained, then the OPA will activate at most two relays.
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In this paper, we develop an energy-efficient resource-allocation scheme with proportional fairness for downlink multiuser orthogonal frequency-division multiplexing (OFDM) systems with distributed antennas. Our aim is to maximize energy efficiency (EE) under the constraints of the overall transmit power of each remote access unit (RAU), proportional fairness data rates, and bit error rates (BERs). Because of the nonconvex nature of the optimization problem, obtaining the optimal solution is extremely computationally complex. Therefore, we develop a low-complexity suboptimal algorithm, which separates subcarrier allocation and power allocation. For the low-complexity algorithm, we first allocate subcarriers by assuming equal power distribution. Then, by exploiting the properties of fractional programming, we transform the nonconvex optimization problem in fractional form into an equivalent optimization problem in subtractive form, which includes a tractable solution. Next, an optimal energy-efficient power-allocation algorithm is developed to maximize EE while maintaining proportional fairness. Through computer simulation, we demonstrate the effectiveness of the proposed low-complexity algorithm and illustrate the fundamental trade off between energy and spectral-efficient transmission designs.
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The p-median problem is often used to locate p service centers by minimizing their distances to a geographically distributed demand (n). The optimal locations are sensitive to geographical context such as road network and demand points especially when they are asymmetrically distributed in the plane. Most studies focus on evaluating performances of the p-median model when p and n vary. To our knowledge this is not a very well-studied problem when the road network is alternated especially when it is applied in a real world context. The aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the density in the road network is alternated. The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 service centers we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000. To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when nodes in the road network increase and p is low. When p is high the improvements are larger. The results also show that choice of the best network depends on p. The larger p the larger density of the network is needed.