Planejamento da expansão de sistemas de transmissão usando a metaheurística de busca em vizinhança variável

Pós-graduação em Engenharia Elétrica - FEIS

Cogeneration design problem Computational complexity analysis and solution through an expert system

Purpose - The purpose of this paper is twofold: to analyze the computational complexity of the cogeneration design problem; to present an expert system to solve the proposed problem, comparing such an approach with the traditional searching methods available.Design/methodology/approach - The complexity of the cogeneration problem is analyzed through the transformation of the well-known knapsack problem. Both problems are formulated as decision problems and it is proven that the cogeneration problem is np-complete. Thus, several searching approaches, such as population heuristics and dynamic programming, could be used to solve the problem. Alternatively, a knowledge-based approach is proposed by presenting an expert system and its knowledge representation scheme.Findings - The expert system is executed considering two case-studies. First, a cogeneration plant should meet power, steam, chilled water and hot water demands. The expert system presented two different solutions based on high complexity thermodynamic cycles. In the second case-study the plant should meet just power and steam demands. The system presents three different solutions, and one of them was never considered before by our consultant expert.Originality/value - The expert system approach is not a "blind" method, i.e. it generates solutions based on actual engineering knowledge instead of the searching strategies from traditional methods. It means that the system is able to explain its choices, making available the design rationale for each solution. This is the main advantage of the expert system approach over the traditional search methods. On the other hand, the expert system quite likely does not provide an actual optimal solution. All it can provide is one or more acceptable solutions.

The open capacitated arc routing problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Using traditional heuristic algorithms on an initial genetic algorithm population applied to the transmission expansion planning problem

This paper analyses the impact of choosing good initial populations for genetic algorithms regarding convergence speed and final solution quality. Test problems were taken from complex electricity distribution network expansion planning. Constructive heuristic algorithms were used to generate good initial populations, particularly those used in resolving transmission network expansion planning. The results were compared to those found by a genetic algorithm with random initial populations. The results showed that an efficiently generated initial population led to better solutions being found in less time when applied to low complexity electricity distribution networks and better quality solutions for highly complex networks when compared to a genetic algorithm using random initial populations.

Global optimization for the ℋ∞-norm model reduction problem

A branch and bound algorithm is proposed to solve the [image omitted]-norm model reduction problem for continuous and discrete-time linear systems, with convergence to the global optimum in a finite time. The lower and upper bounds in the optimization procedure are described by linear matrix inequalities (LMI). Also proposed are two methods with which to reduce the convergence time of the branch and bound algorithm: the first one uses the Hankel singular values as a sufficient condition to stop the algorithm, providing to the method a fast convergence to the global optimum. The second one assumes that the reduced model is in the controllable or observable canonical form. The [image omitted]-norm of the error between the original model and the reduced model is considered. Examples illustrate the application of the proposed method.

Problem of assignment cells to switches in a cellular mobile network via beam search method

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.

Preschool children and excess weight: the impact of a low complexity intervention in public day care centers

Introduction: childhood obesity is a major public health problem, affecting children even at early ages. Objective: to assess the impact of dietary intervention and relatively simple physical activity on the nutritional state of preschoolers. Method: this was an intervention study in public daycare centers targeting children from 2 to 4 years of age, in the State of São Paulo. The sample consisted of 9 daycare centers covering 578 children, with 264 children in the intervention group (IG) and 314 in the comparison group (CG). Intervention was focused on modifications in diet and physical activity, avoiding overloading the routine of daycare centers, for duration of one year. A zBMI score > 1 (zBMI) and < 2 was considered risk of being overweight, and > 2 zBMI was considered excess weight (overweight and obese). Analysis was done by frequency calculations, comparisons of proportions by χ2, mean comparisons by t-student and calculations according to Pearson’s correlation coefficient. Results: IG showed an inverse correlation between the initial zBMI of the children and the difference with the zBMI at the end of the intervention (rP = -0.39, p <0.0001). The mean difference of zBMI of the overweight children in IG between the beginning and the end of the study period was negative (-0.46 z score), indicating weight reduction, while the children in the CG was positive (+0. 17 z score) (p = 0.0037). Conclusion: intervention in diet and physical activity in overweight preschool children in daycare centers could have a favorable impact on the evolution of their nutritional state.