11 resultados para [JEL:D70] Microeconomics - Analysis of Collective Decision-Making - General

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Companies, in general, operate due to the work of its subsystems and this is possible thanks to operational planning that tries to promote the best way to integrate them without giving up the mission, vision and values of the company. The main purpose of a business is to serve customers, but to be successful must take into account other factors such as survival, profitability, growth and operational standpoint to use their resources effectively. The use of tools to support the process of analysis of management decision-making is gaining importance in the context of competitiveness in the world market. The objective of this paper is to present a simulation of the process of forecasting demand to obtain optimal results for a steel company, compare the actual results with order entry and assess the magnitude of the error

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Digital data sets constitute rich sources of information, which can be extracted and evaluated applying computational tools, for example, those ones for Information Visualization. Web-based applications, such as social network environments, forums and virtual environments for Distance Learning, are good examples for such sources. The great amount of data has direct impact on processing and analysis tasks. This paper presents the computational tool Mapper, defined and implemented to use visual representations - maps, graphics and diagrams - for supporting the decision making process by analyzing data stored in Virtual Learning Environment TelEduc-Unesp. © 2012 IEEE.

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We examined how the information communicated by a scout worker influences the plant species transported by recruited workers in Acromymex balzani, Acromyrmex rugosus, and Acromyrmex crassispinus, three species of leaf-cutting ant that have different substrate and habitat preferences. We verified that certain plant species were more likely to be transported than others and that recruitment occurs. We found that recruited workers were more likely to transport non-preferred plant species when they were recruited to these by scout workers. The results suggest that the scout worker can communicate information about plant identity to recruited workers, but that recruited workers integrate the information communicated with their own experience during the decision-making process. (C) 2004 Published by Elsevier B.V.

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The medium term hydropower scheduling (MTHS) problem involves an attempt to determine, for each time stage of the planning period, the amount of generation at each hydro plant which will maximize the expected future benefits throughout the planning period, while respecting plant operational constraints. Besides, it is important to emphasize that this decision-making has been done based mainly on inflow earliness knowledge. To perform the forecast of a determinate basin, it is possible to use some intelligent computational approaches. In this paper one considers the Dynamic Programming (DP) with the inflows given by their average values, thus turning the problem into a deterministic one which the solution can be obtained by deterministic DP (DDP). The performance of the DDP technique in the MTHS problem was assessed by simulation using the ensemble prediction models. Features and sensitivities of these models are discussed. © 2012 IEEE.

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This paper presents the application of artificial immune systems for analysis of the structural integrity of a building. Inspired by a biological process, it uses the negative selection algorithm to perform the identification and characterization of structural failure. This paper presents the application of artificial immune systems for analysis of the structural integrity of a building. Inspired by a biological process, it uses the negative selection algorithm to perform the identification and characterization of structural failure. This methodology can assist professionals in the inspection of mechanical and civil structures, to identify and characterize flaws, in order to perform preventative maintenance to ensure the integrity of the structure and decision-making. In order to evaluate the methodology was made modeling a two-story building and several situations were simulated (base-line condition and improper conditions), yielding a database of signs, which were used as input data for the negative selection algorithm. The results obtained by the present method efficiency, robustness and accuracy.

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In a recent paper, "A combined tool for environmental scientists and decision makers: ternary diagrams and emergy accounting." [Giannettti BF, Barrella FA, Almeida CMVB. A combined tool for environment scientists and decision makers: ternary diagrams and emergy accounting. J Clean Prod, in press http://dx.doi.org/10.1016/j.jclepro.2004.09.002] Ternary diagrams were proposed as a graphical tool to assist emergy analysis. The graphical representation of the emergy accounting data makes it possible to compare processes and systems with and without ecosystem services, to evaluate improvements and to follow the system performance over time. The graphic tool is versatile and adaptable to represent products, processes, systems, countries, and different periods of time.The use and the versatility of ternary diagrams for assisting in performing emergy analyses are illustrated by means of five examples taken from the literature, which are presented and discussed. It is shown that emergetic ternary diagram's properties assist the assessment of the system of the system efficiency, its dependance upon renewable and non-renewable inputs and the environmental support for dilution and abatement of process emissions. With the aid of ternary diagrams, details such as the interaction between systems and between systems and the environment are recognized and evaluated. Such a tool for graphical analysis allows a transparent presentation of the results and can serve as an interface between emergy scientists and decision makers, provided the meaning of each line in the diagram is carefully explained and understood. (c) 2005 Elsevier Ltd. All rights reserved.

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This paper presents the application of artificial neural networks in the analysis of the structural integrity of a building. The main objective is to apply an artificial neural network based on adaptive resonance theory, called ARTMAP-Fuzzy neural network and apply it to the identification and characterization of structural failure. This methodology can help professionals in the inspection of structures, to identify and characterize flaws in order to conduct preventative maintenance to ensure the integrity of the structure and decision-making. In order to validate the methodology was modeled a building of two walk, and from this model were simulated various situations (base-line condition and improper conditions), resulting in a database of signs, which were used as input data for ARTMAP-Fuzzy network. The results show efficiency, robustness and accuracy.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)