The paper presents two new approaches to multiobjective design space exploration for parametric VLSI systems. Both considerably reduce the number of simulations needed to determine the Pareto-optimal set as compared with an exhaustive approach. The first uses sensitivity analysis while the second uses evolutionary computing techniques. Application to a highly parametric system-on-achip for digital camera applications shows the validity of the methodologies presented in terms of both accuracy of results and efficiency, measured as the number of simulations needed to determine the power/execution-time tradeoff front.