We present a comparison of different algorithms to solve the problem of minimizing the expectation of the maximum line length of a multiservice system. One of the features of the problem is that the evaluation of the objective function is computationally heavy. In order to find a numerical solution of the problem, we analyze two representations of the objective function that allow some approximations and compare the efficiency of approximate Monte Carlo and deterministic versions of the gradient projection method. Results of a set of simulations are provided. The algorithms we provide appear to solve accurately the problem much faster than the standard gradient projection method.
Approximate vs. exact algorithms to solve the maximum line length problem
VISCOLANI, BRUNO
2001
Abstract
We present a comparison of different algorithms to solve the problem of minimizing the expectation of the maximum line length of a multiservice system. One of the features of the problem is that the evaluation of the objective function is computationally heavy. In order to find a numerical solution of the problem, we analyze two representations of the objective function that allow some approximations and compare the efficiency of approximate Monte Carlo and deterministic versions of the gradient projection method. Results of a set of simulations are provided. The algorithms we provide appear to solve accurately the problem much faster than the standard gradient projection method.
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