An analytical methodology to efficiently evaluate design alternatives in the conversion of a Common Rail Diesel engine to either CNG dedicated or dual fuel engine has been presented in a previous investigation. The simulation of the dual fuel combustion was performed with a modified version of the KIVA3V code including a modified version of the Shell model and a modified Characteristic Time Combustion model. In the present investigation, this methodology has been validated at two levels. The capability of the simulation code in predicting the emissions trends when changing pilot specification, like injected amount, injection pressure and start of injection, and engine configuration parameters, like compression ratio and axial position of the diesel injector has been verified. The second validation was related to the capability of the proposed computer-aided procedure in finding optimal solutions in a reduced computational time. Therefore, a multi-objective genetic algorithm was run for 100 generations with a population of 50 individuals including the same geometric and control variables taken into account in the first validation. The optimization was aimed at minimizing HC and NOx emissions. Three Pareto solutions selected from the results of the optimization were tested experimentally as a final validation. The potential improvement of the combustion process that can be obtained by optimizing the shape of the bowl is finally addressed in the paper.