There are several behaviors that the failure rate function of a random variable T can take. In this context, the graph of total test time (TTT curve) proposed by Aarset (1987) may be used for obtaining empirical behavior of the function failure rate.
The main application concerns to a new robust optimization package with two major contributions. The first contribution refers to the assessment of the adequacy of probabilistic models through a combination of several statistics, which measure the relative quality of statistical models for a given data set. The second one provides a general purpose optimization method based on meta-heuristics functions for maximizing or minimizing an arbitrary objective function.
In computer science, the PSO is a computational method for optimization of parametric and multiparametric functions. The PSO algorithm is a meta-heuristic method, which has been providing good solutions for problems of global optimization functions with box-constrained. As in most heuristic methods that are inspired by biological phenomena, the PSO method is inspired by the behavior of flying birds. The philosophical idea of the PSO algorithm is based on the collective behavior of birds (particle) in search of food (point of global optimal).
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