This paper proposes a multi-objective structure for the optimization of an engine control unit mapping. In this way, first an integrated engine-vehicle model is developed. The objective functions for the optimization problem can be defined from this model. After describing the structure of the optimization problem, two different multi-objective genetic algorithms, namely distance-based Pareto genetic algorithm and non-dominated sorting genetic algorithm (together with entropy-based multi-objective genetic algorithm), are proposed and implemented. The results demonstrate the superiority of this computerized structure to the manual mapping methods and also more generality of the multi-objective methods compared to single-objective ones.