Modeling systems and nonlinear programming in a research environment

Nonlinear programming (NLP) algorithms are often designed for expert users and users from other fields can find them hard to work with. The paper argues that high level modeling systems can help researchers from other fields use NLP productively. It describes the traditional approach to NLP modeling, outlines its limitations, and shows with examples from a particular modeling system, the General Algebraic Modeling System (GAMS), how the limitations can be removed. Finally, the paper reports on the use of GAMS in a research environment.