The driving forces behind the development of GAMS were the users of mathematical programming who believed in optimization as a powerful and elegant framework for solving real life problems in science and engineering.
At the same time, these users were frustrated by high costs, skill requirements, and an overall low reliability of applying optimization tools.
Most of the system's initiatives and support for new development arose in response to problems in the fields of economics, finance, and chemical engineering, since these disciplines view and understand the world as a mathematical program.
GAMS’s impetus for development arose from the frustrating experience of a large economic modeling group at the World Bank.
Their models just could not be moved to other environments, because special programming knowledge was needed, and data formats and solution methods were not portable.
The idea of an algebraic approach to represent, manipulate, and solve large-scale mathematical models fused old and new paradigms into a consistent and computationally tractable system.
Experience using traditional programming languages to manage those name spaces naturally lead one to think in terms of sets and tuples, and this led to the relational data model.
However, translating this rigorous mathematical representation into the algorithm-specific format required the computation of partial derivatives on very large systems.