PROCEEDINGS IPMU '08
Adaptive Genetic Algorithm control parameter optimization to verify the network protocol performance
J.A. Fernández Prieto, Juan R. Velasco Pérez.
Nowadays, it is important to test
the computer networks under realistic
traffic loads. One approach relies
on integrating a Genetic Algorithm
(GA) with the simulator of
the system under verification. One
of the main problems related to GA
is to find the optimal control parameter
values that it uses. Furthermore,
different values may be
necessary during the course of a
run. Adaptive Genetic Algorithms
(AGAs) have been built that dynamically
adjust selected control parameters
during the course of evolving
a problem solution. In this paper
we present a method of finding and
dynamically adjusting the optimum
probabilities to improve the GA performance
and to drive the generation
of a critical background traffic in a
computer network.
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