Computer modeling and simulation efforts are most useful when they can provide an optimal solution to a problem. Toward this goal we need a vertical hierarchy of algorithmic capabilities and software tools, all of which must work together to make optimal solutions possible. In this presentation we discuss efforts in the Trilinos project to enable optimal solutions for scientific and engineering applications. We discuss how the goal of optimal solutions drives requirements not only for good optimization algorithms but also ever faster and more robust forward solvers and scalable kernels, as well as an abstraction layer to couple solver components.