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Vehicle Routing Problem VRP was applied to resource allocation in a power distribution system with needs for service restoration. The objective function consisted in minimizing the displacement by the fleet of maintenance crew. Some critical constraints were also considered: guaranteeing visits of maintenance crew to all requests from locations with service disruption, priority criteria with three levels of severity to classified failures and MTZ constraint to avoid subtours. The implementation was tested in Augerat instances as well as in others proposed by the authors. An exact technique run with Gusek software using gomory cutting was the first attempt to solve the problem, but results were not satisfactory leaving unvisited nodes, and in some cases the computer ran out of memory. A second approach obtained an initial solution by k-opt heuristic, then separated improvements are performed with two different metaheuristics: simulated annealing SAA and genetic algorithm GA. Results indicate that SAA provides more significant improvements.

The use of wind energy for power electric systems attempts to reduce the dependence on fuel-based energy. With the aim of generating electrical power based on wind energy, it becomes necessary to model and predict wind speed. Wind speed observations are packed with outliers what makes it difficult to propose accurate predictors. This paper presents an experimental comparison of three different methods for making a Kalman filter robust to outliers in the context of one-step-ahead wind speed prediction. Two wind speed databases were used to test the predictive performance of the algorithms. The performance for all the methods is measured in terms of skewness and kurtosis for the predicted signal. The algorithms discussed worked efficiently in a sequential approach, and outperformed the standard Kalman filter.

Many authors have discussed the source of errors in PERT networks as follows: Uncertainty in the mean and variance calculations of (a) activity's durations and (b) total project duration, and its related distributions. Different corrections formulas and procedures were proposed. In the other hand, there's an existing risk of delay related to the project morphology, in terms of the number of activities, shape and complexity of the project network. However, the relationship of network's morphology and the uncertainty of the whole project's duration are poorly studied. In this research, a set of project networks with different morphology were generated and several methods available in literature (original PERT included) were used to estimate the parameters (mean and variance) of total project duration, then comparing them to the Monte Carlo Simulation as a representation of the reality, and the best and most accurate method(s) were chosen.

The combined effects of the hydrostatic pressure and in-growth direction applied electric field on the binding energy of hydrogenic shallow-donor impurity states in parallel-coupled-GaAs- Ga 1 - x Al x As -quantum-well wires are calculated using a variational procedure within the effective-mass and parabolic-band approximations. Results are obtained for several dimensions of the structure, shallow-donor impurity positions, hydrostatic pressure, and applied electric field. Our results suggest that external inputs such us hydrostatic pressure and in-growth direction electric field are two useful tools in order to modify the binding energy of a donor impurity in parallel-coupled-quantum-well wires.