754 resultados para Mathematical problem solving


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In this paper, a method for solving the short term transmission network expansion planning problem is presented. This is a very complex mixed integer nonlinear programming problem that presents a combinatorial explosion in the search space. In order to And a solution of excellent quality for this problem, a constructive heuristic algorithm is presented in this paper. In each step of the algorithm, a sensitivity index is used to add a circuit (transmission line or transformer) or a capacitor bank (fixed or variable) to the system. This sensitivity index is obtained solving the problem considering the numbers of circuits and capacitors banks to be added (relaxed problem), as continuous variables. The relaxed problem is a large and complex nonlinear programming and was solved through a higher order interior point method. The paper shows results of several tests that were performed using three well-known electric energy systems in order to show the possibility and the advantages of using the AC model. ©2007 IEEE.

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The present paper evaluates meta-heuristic approaches to solve a soft drink industry problem. This problem is motivated by a real situation found in soft drink companies, where the lot sizing and scheduling of raw materials in tanks and products in lines must be simultaneously determined. Tabu search, threshold accepting and genetic algorithms are used as procedures to solve the problem at hand. The methods are evaluated with a set of instance already available for this problem. This paper also proposes a new set of complex instances. The computational results comparing these approaches are reported. © 2008 IEEE.

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This paper presents a mathematical model and a methodology to solve a transmission network expansion planning problem considering uncertainty in demand and generation. The methodology used to solve the problem, finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with uncertainty. The model presented results in an optimization problem that is solved using a specialized genetic algorithm. The results obtained for known systems from the literature show that cheaper plans can be found satisfying the uncertainty in demand and generation. ©2008 IEEE.

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The problem of assigning cells to switches in a cellular mobile network is an NP-hard optimization problem. So, real size mobile networks could not be solved by using exact methods. The alternative is the use of the heuristic methods, because they allow us to find a good quality solution in a quite satisfactory computational time. This paper proposes a Beam Search method to solve the problem of assignment cell in cellular mobile networks. Some modifications in this algorithm are also presented, which allows its parallel application. Computational results obtained from several tests confirm the effectiveness of this approach to provide good solutions for medium- and large-sized cellular mobile network.

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We present an educational proposal for the study of combinatorial reasoning and calculation of probabilities based on a game and problem solving methodology, aiming to support the teaching of mathematical content. A review of the literature related to the teaching and learning of the concepts of combinatorial reasoning and probability is presented. The game is original, using a board game similar to Tic-tac-toe, and the movements of its parts have some similarities, in particular those made with the rook and pawn pieces of the game of chess. We formulate various activities (problems) involving the game which, in the process of solving them, using the problem solving methodology and with the appropriate intervention of the teacher, encourage students to develop strategies for counting, an indispensable tool in the initial study of Combinatorial Analysis and Calculation of Probabilities.

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We present in this paper a pedagogical-didactic proposal for the teaching of Laplace Probability. The starting point for building the concept of probability is a game situation associated with the methodology of problem-solving. The theoretical reference for the concept of game is constructivist teaching of mathematics. Mathematical knowledge is constructed based on problems that generate new concepts and / or new content. The proposed game is original. Our proposal can be used both in the last cycle of basic education but also in high school, and may inform the practice of teachers who teach basic concepts of probability.

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Transmission expansion planning (TEP) is a non-convex optimization problem that can be solved via different heuristic algorithms. A variety of classical as well as heuristic algorithms in literature are addressed to solve TEP problem. In this paper a modified constructive heuristic algorithm (CHA) is proposed for solving such a crucial problem. Most of research papers handle TEP problem by linearization of the non-linear mathematical model while in this research TEP problem is solved via CHA using non-linear model. The proposed methodology is based upon Garver's algorithm capable of applying to a DC model. Simulation studies and tests results on the well known transmission network such as: Garver and IEEE 24-bus systems are carried out to show the significant performance as well as the effectiveness of the proposed algorithm. © 2011 IEEE.

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We discuss the knowledge that has been constructed regarding Problem Solving in Math Education as a result of research developed by GTERP - Work and Study Group in Problem Solving, UNESP-Rio Claro/SP. The research is guided by the following general questions: How do students construct mathematical knowledge and how do teachers implement the methodology of Math Teaching-Learning-Evaluation through Problem Solving? Historical aspects of Problem Solving are very important in the configuration of the current trends for Problem Solving. One of them is the Methodology of Math Teaching-Learning- Evaluation through Problem Solving, based on clear foundations and an approach of renewal. In addition to that methodology, two aspects have been developed by the group: The conception of Math as a science of pattern and order and Discrete Mathematics. The knowledge constructed and the scientific production of GTERP prove its relevant contribution to intensifying dialogues between research and educational practice, students and teachers, and to increasing the possibilities of that practice particularly in Math work.

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This paper proposes a new strategy to reduce the combinatorial search space of a mixed integer linear programming (MILP) problem. The construction phase of greedy randomized adaptive search procedure (GRASP-CP) is employed to reduce the domain of the integer variables of the transportation model of the transmission expansion planning (TM-TEP) problem. This problem is a MILP and very difficult to solve specially for large scale systems. The branch and bound (BB) algorithm is used to solve the problem in both full and the reduced search space. The proposed method might be useful to reduce the search space of those kinds of MILP problems that a fast heuristic algorithm is available for finding local optimal solutions. The obtained results using some real test systems show the efficiency of the proposed method. © 2012 Springer-Verlag.

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Goal Programming (GP) is an important analytical approach devised to solve many realworld problems. The first GP model is known as Weighted Goal Programming (WGP). However, Multi-Choice Aspirations Level (MCAL) problems cannot be solved by current GP techniques. In this paper, we propose a Multi-Choice Mixed Integer Goal Programming model (MCMI-GP) for the aggregate production planning of a Brazilian sugar and ethanol milling company. The MC-MIGP model was based on traditional selection and process methods for the design of lots, representing the production system of sugar, alcohol, molasses and derivatives. The research covers decisions on the agricultural and cutting stages, sugarcane loading and transportation by suppliers and, especially, energy cogeneration decisions; that is, the choice of production process, including storage stages and distribution. The MCMIGP allows decision-makers to set multiple aspiration levels for their problems in which the more/higher, the better and the less/lower, the better in the aspiration levels are addressed. An application of the proposed model for real problems in a Brazilian sugar and ethanol mill was conducted; producing interesting results that are herein reported and commented upon. Also, it was made a comparison between MCMI GP and WGP models using these real cases. © 2013 Elsevier Inc.

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Pós-graduação em Engenharia Elétrica - FEB

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)