This paper introduces PareDA (ParetoDesignAutomation), a composite automated methodology for the optimization of analog circuits and solar cell devices. The PareDA framework combines randomized algorithms, domain and constraints sensitivity analysis, epsilon-dominance and global robustness analysis in order to perform simulation-based, multi-scenario and multi-objective optimization. PareDA is evaluated on the problems of designing a three-stage operational amplifier, a yield-aware optimization of a folded-cascode operational amplifier (requiring multiple operating conditions) and a model for selective emitter solar cells.Comparisons with a selection of state-of-the-art techniques (such as NSGA-II and YdIRCO) highlight the effectiveness of PareDA both in terms of Pareto optimality of the solutions found and time-to-converge. The solutions obtained by PareDA dominate those of comparative techniques, in particular, the proposed technique shows a significant average performance improvement (ranging from 35% to 49%) with respect to such techniques. Moreover, the CPU time required by PareDA to converge is smaller of at least 75% if compared with the other methodologies here analyzed (e.g. significantly improved designs for folded-cascode operational amplifier are found in just 320s). Finally, the PareDA algorithm can also benefit from parallelization, which leads to a significant speed-up with respect to the nonparallel version.