813 resultados para Problem Solving Environment


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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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Network reconfiguration is an important tool to optimize the operating conditions of a distribution system. This is accomplished modifying the network structure of distribution feeders by changing the open/close status of sectionalizing switches. This not only reduces the power losses, but also relieves the overloading of the network components. Network reconfiguration belongs to a complex family of problems because of their combinatorial nature and multiple constraints. This paper proposes a solution to this problem, using a specialized evolutionary algorithm, with a novel codification, and a brand new way of implement the genetic operators considering the problem characteristics. The algorithm is presented and tested in a real distribution system, showing excellent results and computational efficiency. © 2007 IEEE.

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This paper presents a new approach to the resolution of the Optimal Power Flow problem. In this approach the inequality constraints are treated by the Modified Barrier and Primal-Dual Logarithmic Barrier methods. The inequality constraints are transformed into equalities by introducing positive auxiliary variables, which are perturbed by the barrier parameter. A Lagrangian function is associated with the modified problem. The first-order necessary conditions are applied to the Lagrangian, generating a nonlinear system which is solved by Newton's method. The perturbation of the auxiliary variables results in an expansion of the feasible set of the original problem, allowing the limits of the inequality constraints to be reached. Numerical tests on the Brazilian CESP and South-Southeast systems and a comparative test indicated that the new approach efficiently resolves of the Optimal Power Flow problem. © 2007 IEEE.

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A lot sizing and scheduling problem prevalent in small market-driven foundries is studied. There are two related decision levels: (1) the furnace scheduling of metal alloy production, and (2) moulding machine planning which specifies the type and size of production lots. A mixed integer programming (MIP) formulation of the problem is proposed, but is impractical to solve in reasonable computing time for non-small instances. As a result, a faster relax-and-fix (RF) approach is developed that can also be used on a rolling horizon basis where only immediate-term schedules are implemented. As well as a MIP method to solve the basic RF approach, three variants of a local search method are also developed and tested using instances based on the literature. Finally, foundry-based tests with a real-order book resulted in a very substantial reduction of delivery delays and finished inventory, better use of capacity, and much faster schedule definition compared to the foundry's own practice. © 2006 Elsevier Ltd. All rights reserved.

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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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Different from the first attempts to solve the image categorization problem (often based on global features), recently, several researchers have been tackling this research branch through a new vantage point - using features around locally invariant interest points and visual dictionaries. Although several advances have been done in the visual dictionaries literature in the past few years, a problem we still need to cope with is calculation of the number of representative words in the dictionary. Therefore, in this paper we introduce a new solution for automatically finding the number of visual words in an N-Way image categorization problem by means of supervised pattern classification based on optimum-path forest. © 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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An enhanced genetic algorithm (EGA) is applied to solve the long-term transmission expansion planning (LTTEP) problem. The following characteristics of the proposed EGA to solve the static and multistage LTTEP problem are presented, (1) generation of an initial population using fast, efficient heuristic algorithms, (2) better implementation of the local improvement phase and (3) efficient solution of linear programming problems (LPs). Critical comparative analysis is made between the proposed genetic algorithm and traditional genetic algorithms. Results using some known systems show that the proposed EGA presented higher efficiency in solving the static and multistage LTTEP problem, solving a smaller number of linear programming problems to find the optimal solutions and thus finding a better solution to the multistage LTTEP problem. Copyright © 2012 Luis A. Gallego et al.

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Introduction: The World Health Organization considers pharmaceutical care (PC) of fundamental importance for the patient and the community. Its exercise requires knowledge and skills, which can be acquired in academic and/or continuing educations, credited for effectiveness and impact evaluation. However, few manuscripts in the literature have showed the contribution of the educational interventions on the knowledge, skill and attitude of students and professionals who participate in scientifi c events related to PC. Objective: To evaluate the impact of an educational intervention (EI), and its degree of satisfaction, to pharmacists and pharmacy students. Method: A quasi-experimental study was performed, through an extension course with 40 hours of lectures approaching issues related to PC and clinical pharmacy (CP). Participants answered a survey which was handed out before and after the EI. The statistic tests of Sinais and Mann-Whitney were applied to evaluate the EI signifi cance. Results: Participants (n= 49) were mostly (n= 34) students and performing activities related to PC and CP (n= 20). Statistics differences, before and after the EI, were found in the scores of knowledge, skill and attitude (p <0.001). The evaluated item which showed the most improvement was the last one. Most (n= 30) had exceeded or met their expectations (n= 19). Conclusions: The analysis of the data led us to conclude that an EI of 40 h/week about knowledge, skill and attitude in PC using traditional methods, improves knowledge and problem-solving skills of participants. ©2012 Ediciones Mayo, S.A. All rights reserved.

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The aim was to identify the perception of Oral Health Planning (OHP) of basic care (BC) dental surgeons (DSs) in João Pessoa, Paraíba State, Brazil. Seventeen BC DSs from João Pessoa were interviewed. A qualitative analysis was performed using the Discourse of the Collective Subject (DCS) methodology. DCS obtained: Impact - My work is effective when the user's need remains at the BC. Social Control - The population participates in the organization of promotional activities, but I think it doesn't have enough maturity to opine on OHP. OHP Basis and Organization - The OHP has a diverse organization and is based on user needs. It can be concluded that the knowledge of the DSs on OHP is varied. There is limited understanding about problem-solving. Social control is considered incipient and weak. It is understood that the organization of the local OHP assumes a diverse character and should be based on user demands.

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Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be in-viable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the bats behaviour, which has never been applied to this context so far. The wrapper approach combines the power of exploration of the bats together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in five public datasets have demonstrated that the proposed approach can outperform some well-known swarm-based techniques. © 2012 IEEE.

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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.