General Algebraic Modeling System - History

History

Initial research and development of GAMS was funded by the International Bank for Reconstruction and Development, usually referred to as The World Bank, through the Bank’s Research Committee (RPO 671-58, RPO 673-06) and carried out at the Development Research Center in Washington, D.C. Since 1987, R&D has been funded by GAMS Development Corporation.

The system was developed in close cooperation between mathematical economists who are an important group of GAMS users. The synergy between economics, computer science and operations research was the most important factor of success mail in the development of the system. Mathematical programming and economics theory are closely intertwined. The Nobel Prize in Economics awarded to Leonid Kantorovich and Tjalling Koopmans in 1975 for their “contribution to the theory of optimal allocation of resources” was really a prize in mathematical programming. Other Nobel laureates like Kenneth Arrow in 1972, Wassily Leontief in 1973, and Harry Markowitz in 1990 are well known names in math programming. Another early example of this synergy is the use of LP in refining operations, which was started by Alan Manne, an economist, with his book on Scheduling of Petroleum Refinery Operations in 1956.

The origins of linear programming algorithms stem from George Dantzig’s early work in the 1940s and 1950s. Computing technology and algorithmic theory had developed at a rapid pace. Thirty years later, it was possible to solve problems of practical size and complexity that allowed the user to test the economic theory on real life problems. The World Bank's research agenda in the 1970s and 1980s created the perfect environment to bring different disciplines together in order to apply mathematical programming to research and operational questions in Economic Development.

The focus and technical constraints of the development of modeling systems have changed in the last 30 years. The dominant constraints in the first phase were the computational limits of algorithms. Problem representation had to abide by algorithmic convenience, centralized expert groups managed large, expensive and long lasting projects and end users were effectively left out. The second phase focused the model. This volume is about languages and systems supporting this stage. Applications are limited by modeling skill, project groups are much smaller and decentralized, the computational cost are low and the users are involved in the design of the application. Applications are designed to be independent of computing platforms and frequently operate in a client-server environment. The next step was to ameliorate the application as well as the optimization model. These are just one of many analytic tools that help making better decisions. User interfaces are built with off-the-shelf components and frequently change to adjust to evolving environments and new computing technologies. Currently the UI is only available for Windows.

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