The optimization approach seems promising for the consistent initialization of DAEs for it can be applied to the resolution of over-determined or ill-conditioned algebraic consistency systems. Given the DAE system and all the additional constraints (feasible or not) that the user may impose, it must be found a set of initial conditions as close as possible to a consistent one. In other words, the deviation from the equations and constraints must be minimized in some norm. The choice of the optimization method is crucial for the successful implementation of the code. Derivative-based optimization methods and stochastic optimization methods are quite different techniques, with different drawbacks and potentialities. When combined, these strategies generally lead to very efficient search and optimization tools. There has been a growing interest in heuristic optimization methods since the emergence of massively parallel computers. However, the impact of such techniques on the dynamic simulation of chemical engineering systems - particularly in the initialization problem - has not been sufficiently studied. In several classes of important problems traditional optimization techniques may fail. due to either high computational cost or inherent limitations of gradient-type methods. A preliminary DAE initialization code using the optimization approach and a heuristic optimization algorithm, under development at PEQ/COPPE/UFRJ, is presented in this work. The code has been tested in some chemical engineering applications. Simple models frequently adopted in the DAE literature were used to provide a kind of benchmark for the initialization problem.