969 resultados para Supplier selection problem
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Materials selection is a matter of great importance to engineering design and software tools are valuable to inform decisions in the early stages of product development. However, when a set of alternative materials is available for the different parts a product is made of, the question of what optimal material mix to choose for a group of parts is not trivial. The engineer/designer therefore goes about this in a part-by-part procedure. Optimizing each part per se can lead to a global sub-optimal solution from the product point of view. An optimization procedure to deal with products with multiple parts, each with discrete design variables, and able to determine the optimal solution assuming different objectives is therefore needed. To solve this multiobjective optimization problem, a new routine based on Direct MultiSearch (DMS) algorithm is created. Results from the Pareto front can help the designer to align his/hers materials selection for a complete set of materials with product attribute objectives, depending on the relative importance of each objective.
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A função de escalonamento desempenha um papel importante nos sistemas de produção. Os sistemas de escalonamento têm como objetivo gerar um plano de escalonamento que permite gerir de uma forma eficiente um conjunto de tarefas que necessitam de ser executadas no mesmo período de tempo pelos mesmos recursos. Contudo, adaptação dinâmica e otimização é uma necessidade crítica em sistemas de escalonamento, uma vez que as organizações de produção têm uma natureza dinâmica. Nestas organizações ocorrem distúrbios nas condições requisitos de trabalho regularmente e de forma inesperada. Alguns exemplos destes distúrbios são: surgimento de uma nova tarefa, cancelamento de uma tarefa, alteração na data de entrega, entre outros. Estes eventos dinâmicos devem ser tidos em conta, uma vez que podem influenciar o plano criado, tornando-o ineficiente. Portanto, ambientes de produção necessitam de resposta imediata para estes eventos, usando um método de reescalonamento em tempo real, para minimizar o efeito destes eventos dinâmicos no sistema de produção. Deste modo, os sistemas de escalonamento devem de uma forma automática e inteligente, ser capazes de adaptar o plano de escalonamento que a organização está a seguir aos eventos inesperados em tempo real. Esta dissertação aborda o problema de incorporar novas tarefas num plano de escalonamento já existente. Deste modo, é proposta uma abordagem de otimização – Hiper-heurística baseada em Seleção Construtiva para Escalonamento Dinâmico- para lidar com eventos dinâmicos que podem ocorrer num ambiente de produção, a fim de manter o plano de escalonamento, o mais robusto possível. Esta abordagem é inspirada em computação evolutiva e hiper-heurísticas. Do estudo computacional realizado foi possível concluir que o uso da hiper-heurística de seleção construtiva pode ser vantajoso na resolução de problemas de otimização de adaptação dinâmica.
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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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This comment corrects the errors in the estimation process that appear in Martins (2001). The first error is in the parametric probit estimation, as the previously presented results do not maximize the log-likelihood function. In the global maximum more variables become significant. As for the semiparametric estimation method, the kernel function used in Martins (2001) can take on both positive and negative values, which implies that the participation probability estimates may be outside the interval [0,1]. We have solved the problem by applying local smoothing in the kernel estimation, as suggested by Klein and Spady (1993).
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This paper revisits the problem of adverse selection in the insurance market of Rothschild and Stiglitz [28]. We propose a simple extension of the game-theoretic structure in Hellwig [14] under which Nash-type strategic interaction between the informed customers and the uninformed firms results always in a particular separating equilibrium. The equilibrium allocation is unique and Pareto-efficient in the interim sense subject to incentive-compatibility and individual rationality. In fact, it is the unique neutral optimum in the sense of Myerson [22].
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The paper discusses the utilization of new techniques ot select processes for protein recovery, separation and purification. It describesa rational approach that uses fundamental databases of proteins molecules to simplify the complex problem of choosing high resolution separation methods for multi component mixtures. It examines the role of modern computer techniques to help solving these questions.
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How cells polarize in response to external cues is a fundamental biological problem. For mating, yeast cells orient growth toward the source of a pheromone gradient produced by cells of the opposite mating type. Polarized growth depends on the small GTPase Cdc42, a central eukaryotic polarity regulator that controls signaling, cytoskeleton polarization, and vesicle trafficking. However, the mechanisms of polarity establishment and mate selection in complex cellular environments are poorly understood. Here we show that, in fission yeast, low-level pheromone signaling promotes a novel polarization state, where active Cdc42, its GEF Scd1, and scaffold Scd2 form colocalizing dynamic zones that sample the periphery of the cell. Two direct Cdc42 effectors--actin cables marked by myosin V Myo52 and the exocyst complex labeled by Sec6 and Sec8--also dynamically colocalize with active Cdc42. However, these cells do not grow due to a block in the exocytosis of cell wall synthases Bgs1 and Bgs4. High-level pheromone stabilizes active Cdc42 zones and promotes cell wall synthase exocytosis and polarized growth. However, in the absence of prior low-level pheromone signaling, exploration fails, and cells polarize growth at cell poles by default. Consequently, these cells show altered partner choice, mating preferentially with sister rather than nonsister cells. Thus, Cdc42 exploration serves to orient growth for partner selection. This process may also promote genetic diversification.
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We study the interaction between nonprice public rationing and prices in the private market. Under a limited budget, the public supplier uses a rationing policy. A private firm may supply the good to those consumers who are rationed by the public system. Consumers have different amounts of wealth, and costs of providing the good to them vary. We consider two regimes. First, the public supplier observes consumers' wealth information; second, the public supplier observes both wealth and cost information. The public supplier chooses a rationing policy, and, simultaneously, the private firm, observing only cost but not wealth information, chooses a pricing policy. In the first regime, there is a continuum of equilibria. The Pareto dominant equilibrium is a means-test equilibrium: poor consumers are supplied while rich consumers are rationed. Prices in the private market increase with the budget. In the second regime, there is a unique equilibrium. This exhibits a cost-effectiveness rationing rule; consumers are supplied if and only if their costbenefit ratios are low. Prices in the private market do not change with the budget. Equilibrium consumer utility is higher in the cost-effectiveness equilibrium than the means-test equilibrium [Authors]
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One of the important questions in biological evolution is to know if certain changes along protein coding genes have contributed to the adaptation of species. This problem is known to be biologically complex and computationally very expensive. It, therefore, requires efficient Grid or cluster solutions to overcome the computational challenge. We have developed a Grid-enabled tool (gcodeml) that relies on the PAML (codeml) package to help analyse large phylogenetic datasets on both Grids and computational clusters. Although we report on results for gcodeml, our approach is applicable and customisable to related problems in biology or other scientific domains.
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We propose an edge detector based on the selection of wellcontrasted pieces of level lines, following the proposal ofDesolneux-Moisan-Morel (DMM) [1]. The DMM edge detectorhas the problem of over-representation, that is, everyedge is detected several times in slightly different positions.In this paper we propose two modifications of the originalDMM edge detector in order to solve this problem. The firstmodification is a post-processing of the output using a generalmethod to select the best representative of a bundle of curves.The second modification is the use of Canny’s edge detectorinstead of the norm of the gradient to build the statistics. Thetwo modifications are independent and can be applied separately.Elementary reasoning and some experiments showthat the best results are obtained when both modifications areapplied together.
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It has long been standard in agency theory to search for incentive-compatible mechanisms on the assumption that people care only about their own material wealth. However, this assumption is clearly refuted by numerous experiments, and we feel that it may be useful to consider nonpecuniary utility in mechanism design and contract theory. Accordingly, we devise an experiment to explore optimal contracts in an adverse-selection context. A principal proposes one of three contract menus, each of which offers a choice of two incentive-compatible contracts, to two agents whose types are unknown to the principal. The agents know the set of possible menus, and choose to either accept one of the two contracts offered in the proposed menu or to reject the menu altogether; a rejection by either agent leads to lower (and equal) reservation payoffs for all parties. While all three possible menus favor the principal, they do so to varying degrees. We observe numerous rejections of the more lopsided menus, and approach an equilibrium where one of the more equitable contract menus (which one depends on the reservation payoffs) is proposed and agents accept a contract, selecting actions according to their types. Behavior is largely consistent with all recent models of social preferences, strongly suggesting there is value in considering nonpecuniary utility in agency theory.
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It has long been standard in agency theory to search for incentive-compatible mechanisms on the assumption that people care only about their own material wealth. However, this assumption is clearly refuted by numerous experiments, and we feel that it may be useful to consider nonpecuniary utility in mechanism design and contract theory. Accordingly, we devise an experiment to explore optimal contracts in an adverse-selection context. A principal proposes one of three contract menus, each of which offers a choice of two incentive-compatible contracts, to two agents whose types are unknown to the principal. The agents know the set of possible menus, and choose to either accept one of the two contracts offered in the proposed menu or to reject the menu altogether; a rejection by either agent leads to lower (and equal) reservation payoffs for all parties. While all three possible menus favor the principal, they do so to varying degrees. We observe numerous rejections of the more lopsided menus, and approach an equilibrium where one of the more equitable contract menus (which one depends on the reservation payoffs) is proposed and agents accept a contract, selecting actions according to their types. Behavior is largely consistent with all recent models of social preferences, strongly suggesting there is value in considering nonpecuniary utility in agency theory.
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Given $n$ independent replicates of a jointly distributed pair $(X,Y)\in {\cal R}^d \times {\cal R}$, we wish to select from a fixed sequence of model classes ${\cal F}_1, {\cal F}_2, \ldots$ a deterministic prediction rule $f: {\cal R}^d \to {\cal R}$ whose risk is small. We investigate the possibility of empirically assessingthe {\em complexity} of each model class, that is, the actual difficulty of the estimation problem within each class. The estimated complexities are in turn used to define an adaptive model selection procedure, which is based on complexity penalized empirical risk.The available data are divided into two parts. The first is used to form an empirical cover of each model class, and the second is used to select a candidate rule from each cover based on empirical risk. The covering radii are determined empirically to optimize a tight upper bound on the estimation error. An estimate is chosen from the list of candidates in order to minimize the sum of class complexity and empirical risk. A distinguishing feature of the approach is that the complexity of each model class is assessed empirically, based on the size of its empirical cover.Finite sample performance bounds are established for the estimates, and these bounds are applied to several non-parametric estimation problems. The estimates are shown to achieve a favorable tradeoff between approximation and estimation error, and to perform as well as if the distribution-dependent complexities of the model classes were known beforehand. In addition, it is shown that the estimate can be consistent,and even possess near optimal rates of convergence, when each model class has an infinite VC or pseudo dimension.For regression estimation with squared loss we modify our estimate to achieve a faster rate of convergence.
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Donors often rely on local intermediaries to deliver benefits to target beneficiaries. Each selected recipient observes if the intermediary under-delivers to them, so they serve as natural monitors. However, they may withhold complaints when feeling unentitled or grateful to the intermediary for selecting them. Furthermore, the intermediary may distort selection (e.g. by picking richer recipients who feel less entitled) to reduce complaints. We design an experimental game representing the donor s problem. In one treatment, the intermediary selects recipients. In the other, selection is random - as by an uninformed donor. In our data, random selection dominates delegation of the selection task to the intermediary. Selection distortions are similar, but intermediaries embezzle more when they have selection power and (correctly) expect fewer complaints.
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Sexual selection theory has primarily focussed on the role of mating preferences for the best individuals in the evolution of condition-dependent ornaments, traits that signal absolute quality. Because the most suitable mate for one individual is not always the best for others, however, we argue that non-directional mate choice can promote the evolution of alternative morphs that are not condition-dependent in their expression (i.e. genetic polymorphism). We list the different mate-choice rules (i.e. all individuals have the same preference; preference depends on the chooser's morph; individuals mate preferentially with conspecifics displaying an uncommon or the most frequent morph) and review experimental studies that investigated mate choice in natural populations of colour-polymorphic animals. Our review emphasises that although the experimental data support the idea that sexual selection plays an important role in the evolution of genetic colour polymorphism in many different ways, little is known about the adaptive value of each mate-choice strategy and about their implication in the evolutionary stability of colour polymorphism. One way of solving this problem is to determine the adaptive function of colour morphs, a worthwhile objective, because better understanding of mate-choice rules in polymorphic species should provide important insights into sexual-selection processes and, in turn, into the maintenance of genetic variation.