19 resultados para collaborative planning


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Ameloblastoma is a benign locally aggressive infiltrative odontogenic lesion. It is characterized by slow growth and painless swelling. The treatment for ameloblastoma varies from curettage to en bloc resection, and the reported recurrence rates after treatment are high; the safety margin of resection is important to avoid recurrence. Advances in technology brought about great benefits in dentistry; a new generation of computed tomography scanners and 3-dimensional images enhance the surgical planning and management of maxillofacial tumors. The development of new prototyping systems provides accurate 3D biomodels on which surgery can be simulated, especially in cases of ameloblastoma, in which the safety margin is important for treatment success. A case of mandibular follicular ameloblastoma is reported where a 3D biomodel was used before and during surgery.

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In this paper we present a genetic algorithm with new components to tackle capacitated lot sizing and scheduling problems with sequence dependent setups that appear in a wide range of industries, from soft drink bottling to food manufacturing. Finding a feasible solution to highly constrained problems is often a very difficult task. Various strategies have been applied to deal with infeasible solutions throughout the search. We propose a new scheme of classifying individuals based on nested domains to determine the solutions according to the level of infeasibility, which in our case represents bands of additional production hours (overtime). Within each band, individuals are just differentiated by their fitness function. As iterations are conducted, the widths of the bands are dynamically adjusted to improve the convergence of the individuals into the feasible domain. The numerical experiments on highly capacitated instances show the effectiveness of this computational tractable approach to guide the search toward the feasible domain. Our approach outperforms other state-of-the-art approaches and commercial solvers. (C) 2009 Elsevier Ltd. All rights reserved.

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Two fundamental processes usually arise in the production planning of many industries. The first one consists of deciding how many final products of each type have to be produced in each period of a planning horizon, the well-known lot sizing problem. The other process consists of cutting raw materials in stock in order to produce smaller parts used in the assembly of final products, the well-studied cutting stock problem. In this paper the decision variables of these two problems are dependent of each other in order to obtain a global optimum solution. Setups that are typically present in lot sizing problems are relaxed together with integer frequencies of cutting patterns in the cutting problem. Therefore, a large scale linear optimizations problem arises, which is exactly solved by a column generated technique. It is worth noting that this new combined problem still takes the trade-off between storage costs (for final products and the parts) and trim losses (in the cutting process). We present some sets of computational tests, analyzed over three different scenarios. These results show that, by combining the problems and using an exact method, it is possible to obtain significant gains when compared to the usual industrial practice, which solve them in sequence. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

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Understanding the scientific method fosters the development of critical thinking and logical analysis of information. Additionally, proposing and testing a hypothesis is applicable not only to science, but also to ordinary facts of daily life. Knowing the way science is done and how its results are published is useful for all citizens and mandatory for science students. A 60-h course was created to offer undergraduate students a framework in which to learn the procedures of scientific production and publication. The course`s main focus was biochemistry, and it was comprised of two modules. Module I dealt with scientific articles, and Module II with research project writing. Module I covered the topics: 1) the difference between scientific knowledge and common sense, 2) different conceptions of science, 3) scientific methodology, 4) scientific publishing categories, 5) logical principles, 6) deductive and inductive approaches, and 7) critical reading of scientific articles. Module II dealt with 1) selection of an experimental problem for investigation, 2) bibliographic revision, 3) materials and methods, 4) project writing and presentation, 5) funding agencies, and 6) critical analysis of experimental results. The course adopted a collaborative learning strategy, and each topic was studied through activities performed by the students. Qualitative and quantitative course evaluations with Likert questionnaires were carried out at each stage, and the results showed the students` high approval of the course. The staff responsible for course planning and development also evaluated it positively. The Biochemistry Department of the Chemistry Institute of the University of Sao Paulo has offered the course four times.