Adaptive Genetic Algorithm control parameter optimization to verify the network protocol performance
J.A. Fernández-Prieto, Juan Ramón Velasco Pérez · 2008
Nowadays, it is important to test the computer networks under real-istic traffic loads. One approach re-lies on integrating a Genetic Algo-rithm (GA) with the simulator of the system under verification. One of the main problems related to GA is to find the optimal control pa-rameter values that it uses. Fur-thermore, different values may be necessary during the course of a run. Adaptive Genetic Algorithms (AGAs) have been built that dynam-ically adjust selected control param-eters 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 per-formance and to drive the generation of a critical background traffic in a computer network.