Air traffic growth and especially hubs development cause new significant congestion and ground delays on major airports. Accurate models of airport traffic prediction can provide new tools to assist gr ound controllers in choosing the best taxiways and the most adapted holding points for aircraft. Such tools could also be used by airport designers to evaluate possible improvements on airport configurations and airpor t structure. In this paper, a ground traffic simulation tool is proposed and applied to Roissy Charles De Gaulle and Orly airports. A global optimization method using genetic algorithms is compared to a 1-to-n strategy to minimize time spent between gate and runway, while respecting aircraft separation and runway capacity. In order to compare the efficiency of the different optimization methods, simulations are carried out on a one day traffic sample, and ground delay due to holding points or taxiway lengthening is correlated to the traffic density on the airport.