José Eduardo Souza de Cursi

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The optimization model presented in this paper sets the district boundaries and seeks the best #eet of vehicles as to minimize total daily transport costs. Both vehicle time and vehicle load are treated probabilistically. Each district is related to a characteristic function that takes into account distribution costs, time and capacity constraints,(More)
Facility location problems are frequent in OR literature. In districting problems, on the other hand, the aim is to partition a territory into smaller units, called districts or zones, while an objective function is optimized and some constraints are satisfied, such as balance, contiguity, and compactness. Although many location and districting problems(More)
We consider the global optimization of a nonsmooth (nondifferentiable) nonconvex real function. We introduce a variable metric descent method adapted to nonsmooth situations, which is modified by the incorporation of suitable random perturbations. Convergence to a global minimum is established and a simple method for the generation of suitable perturbations(More)
Reliability analysis is often based on stochastic d iscrete event models like stochastic Petri Nets. For complex dynamical systems with numerous compone nts, analytical expressions of the steady state are tedious to work out because of the combinatory explosion with discrete models. For this reason, fluidification is an interesting alternative to est imate(More)
This work aims at developing a genetic algorithm (GA) to pursue the optimization of hybrid laminated composite structures. Fiber orientation (predefined ply angles), material (glass-epoxy or carbon-epoxy layer) and total number of plies are considered as design variables. The GA is chosen as an optimization tool because of its ability to deal with(More)
1. Abstract Global optimization problems involve essential difficulties as, for instance, avoiding convergence to local minima. A large variety of methods for global optimization has been proposed in the literature, where stochastic and deterministic approaches may be found. In order to get several solutions, population based methods (such as evolutionary(More)
We present a random perturbation of the projected variable metric method for solving linearly constrained nonsmooth (i.e., nondifferentiable) nonconvex optimization problems, and we establish the convergence to a global minimum for a locally Lipschitz continuous objective function which may be nondifferentiable on a countable set of points. Numerical(More)
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