Tissue engineered vascular grafts can offer long-term benefits in matching the geometry, properties, and function of native blood vessels. Yet, choosing appropriate design parameters for biodegradeable scaffolds such that they evolve into neovessels with favorable characteristics is challenging with iterative experimental testing alone. Herein, we present an in silico framework for constrained optimization of scaffold microstructure, mechanical behavior, and degradation kinetics. Our approach combines a biomechanical model of growth and remodeling informed by large animal experiments with numerical optimization to identify design parameters that limit clinically relevant failure modes, including stenosis and dilatation, and improve functional matching to native vessel compliance. Towards this end, constraints on geometry were introduced as a straightforward way to prevent adverse remodeling outcomes and shown to be useful in shaping desired outcomes in graft remodeling. Our simulations of long-term graft evolution suggest the need for a modest initial immune response to ensure graded load transfer from polymer to neotissue and to prevent extreme changes in diameter. Optimized designs showed less sensitivity to simulated variability in their design parameters, which could limit subject-to-subject variability. Together, these findings highlight the utility of computational modeling in identifying candidate designs for improved outcomes in tissue engineered vascular grafts - elimination of stenosis/aneurysm, better compliance matching, and consistent changes in behavior over time.