This chapter investigates the use of multiobjective optimization to support integrated molecular and process design in two new research frontiers pertaining to efficient process operation as well as computations in grid and cloud computing environments. In the first frontier, we propose a new framework supporting the integration of molecular design and selection with process operation at conditions other than the nominal design settings. The framework combines multiobjective decision-making with a systematic nonlinear sensitivity analysis approach to identify molecular and process characteristics that exhibit reduced sensitivity to external or internal process variability. In the second frontier, we propose the use of this framework in advanced grid and cloud computing environments to improve the efficiency of the necessary computations and to support automated decision-making through user interfaces and workflows that allow the interoperation of heterogeneous design tools. The proposed framework is offered in a software-as-a-service approach where molecular and process design tools as well as multiobjective decision making and sensitivity analysis tools exploit distributed resources under the coordination of dedicated middleware services accessed through a web interface. The proposed developments are illustrated through applications in heat-to-power generation systems (Organic Rankine Cycles) and industrial separations.