998 resultados para PESQUISA OPERACIONAL
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Engenharia Mecânica - FEG
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O objetivo desta pesquisa é propor um modelo numérico prognóstico que trate a variável “tempo” de forma eficiente e eficaz, com a finalidade de atender às reais necessidades dos clientes-usuários e à sociedade em geral. Todavia, realizou-se um levantamento bibliográfico sobre gestão pública, no tocante a obras públicas, estatística e pesquisa operacional para sistema organizacional, visando à modelagem numérica. A pesquisa foi baseada em metodologias quantitativas, com ênfase na pesquisa operacional para o estudo das obras públicas executadas sob a gerência da Prefeitura (PCU) da Universidade Federal do Pará (UFPA). Para a elaboração da base de dados, foram coletados informações de obras, reformas e ampliações, executadas durante o período de 2006 a 2009, junto à Comissão Permanente de Licitação (CPL) e à Fundação de Amparo ao Desenvolvimento da Pesquisa (FADESP). Mediante as regressões lineares e, após as transformadas das funções, foram obtidos para o modelo prognóstico os parâmetros estatísticos: coeficiente de correlação (R), de 0,899; coeficiente de determinação (R²), de 0,808; coeficiente de determinação ajustado (R² ajustado), de 0,796; e erro padrão (Se), de 0,41. Esses parâmetros demonstram forte correlação linearizada entre as variáveis, indicando que 79,60% da variabilidade do tempo para executar uma obra pública é causada ou produzida pela variação, em conjunto, da área; do valor orçado; da capacidade técnica operacional da IFES; da capacidade operacional da empresa; da tipologia de serviço; e da estação do ano. Com os resultados obtidos, conclui-se que é possível aplicar e implementar o modelo prognóstico para execução de obras públicas, pois se obteve uma ferramenta potente em sua aplicação para as melhorias dos procedimentos administrativos, tanto na estrutura como no seu desempenho, cujo principal resultado é a previsão do tempo para execução do empreendimento público.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Engenharia Elétrica - FEIS
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The archival institutions should for the elevation of the statistical indices of social and economic to integrate with sustainable development yours communities through regional entrepreneurship and improving informational. The Commerce and Industry Association of Marília (ACIM) archive provided to analyze the influence of the files on regional growth to development sustainable of industries and trade. The management theory and archives processes, set up data to create a model template guiding sustainable which suggested the results provided for: Transparency in the processes; global and local integration; culture and collaboration of the community; physical and human factors; improvement for work management and; to utilized to generate the economy of the ecosystem as a form of natural resources.
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Organizational change is occurring in the Brazilian agribusiness from sugar cane in recent decades. Aspects of management in this sector are being changed due to the importance of its products, especially ethanol and electricity. It is observed in the literature a lack of quantitative studies in this Brazilian sector, particularly the selection of sugarcane varieties for planting. This study proposes the use of Goal Programming (GP) with Data Envelopment Analysis (DEA) to select efficient varieties of sugarcane for planting in a sugar and ethanol milling company. The study allowed the identification of efficient sugarcane varieties. This way, it helped the company to make more reliable decisions, favoring the increase of productivity
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The competition among companies nowadays, caused by globalization and with customers more and more demanding, makes the companies rethink their strategies for survival. To improve their competition the companies are adopting management tool to improve the manufacturing management, which is considered a key to success. The present study aimed to develop a method, based on techniques of theory of constraints and operational research, to ensure the best use of resources and best decision of a production line on a steel company, with focus in the customers’ delivery time, which is a requirement of the current market. The conclusion of this study is that the correct use of the management tools, such as theory of constraints and operational research, can ensure a long survival for the companies that duel for the market share, especially in regard to customers’ delivery time, that generates their satisfaction
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This work is quantified according to the ABEPRO areas, the number of works the Course Conclusion (TCCs) and Hours (CH) Course of Production Engineering, UNESP Guaratinguetá. Based on this quantification were found to be significant discrepancies between the TCCs and CH. Quality and Logistics observed for the larger discrepancies, with 26% and 17% of the number of TCCs, respectively. Both areas have only 6% of the time. They are also used data from researchers at the National Council of Scientific and Technological Development (CNPq) in the areas of Production Engineering. In the area of Quality and Logistics, the researchers account for 8% and 5%, respectively, but are most prominent researchers in the field of Operations Research, with 37%. However, this view can help the department to organize the curriculum, with the development of teaching projects, methods and means of education, and visibility to help future hiring for the department
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The vehicle routing problem is to nd a better route to meet a set of customers who are geographically dispersed using vehicles that are a central repository to which they return after serving customers. These customers have a demand that must be met. Such problems have a wide practical application among them we can mention: school transport, distribution of newspapers, garbage collection, among others. Because it is a classic problem as NP-hard, these problems have aroused interest in the search for viable methods of resolution. In this paper we use the Genetic Algorithm as a resolution
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The Set Covering Problem (SCP) plays an important role in Operational Research since it can be found as part of several real-world problems. In this work we report the use of a genetic algorithm to solve SCP. The algorithm starts with a population chosen by a randomized greedy algorithm. A new crossover operator and a new adaptive mutation operator were incorporated into the algorithm to intensify the search. Our algorithm was tested for a class of non-unicost SCP obtained from OR-Library without applying reduction techniques. The algorithms found good solutions in terms of quality and computational time. The results reveal that the proposed algorithm is able to find a high quality solution and is faster than recently published approaches algorithm is able to find a high quality solution and is faster than recently published approaches using the OR-Library.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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In this paper a mathematical model that combines lot-sizing and cutting-stock problems applied to the furniture industry is presented. The model considers the usual decisions of the lot sizing problems, as well as operational decisions related to the cutting machine programming. Two sets of a priori generated cutting patterns are used, industry cutting patterns and a class of n-group cutting patterns. A strategy to improve the utilization of the cutting machine is also tested. An optimization package was used to solve the model and the computational results, using real data from a furniture factory, show that a small subset of n-group cutting patterns provides good results and that the cutting machine utilization can be improved by the proposed strategy.
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In this paper we deal with the one-dimensional integer cutting stock problem, which consists of cutting a set of available objects in stock in order to produce ordered smaller items in such a way as to optimize a given objective function, which in this paper is composed of three different objectives: minimization of the number of objects to be cut (raw material), minimization of the number of different cutting patterns (setup time), minimization of the number of saw cycles (optimization of the saw productivity). For solving this complex problem we adopt a multiobjective approach in which we adapt, for the problem studied, a symbiotic genetic algorithm proposed in the literature. Some theoretical and computational results are presented.