As sector programming models have increased in number, they have also increased, individually, in size and complexity. This increased sophistication has presented to researchers well-defined and difficult choices, the resolution of which usually involves compromise of either model generality or theoretical rigor. This paper discusses problems typical of those encountered in construction of large-scale programming models, and presents an overview of the goals of such models and the uses to which they have been applied.