GAMS available on the Amazon Elastic Compute Cloud 2009 GAMS supports extended mathematical programs (EMP) 2010 GAMS is awarded the company award of the German Society of Operations Research (GOR) 2010 GDXMRW interface between GAMS and Matlab 2010 End of support for Mac PowerPC / Dec Alpha / SGI IRIX / HP-9000/HP-UX 2011 Support for Extrinsic Function Libraries 2011 End of support for Win95 / 98 / ME, and Win2000 2012 The Winners of the 2012 INFORMS Impact Prize included Alexander Meeraus. The prize was awarded to the originators of the five most important algebraic modeling languages. 2012 Introduction of Object Oriented API for .NET, Java, and Python 2012 The winners of the 2012 Coin OR Cup included Michael Bussieck, Steven Dirkse, & Stefan Vigerske for GAMSlinks 2012 End of support for 32 bit on Mac OS X 2013 Support for distributed MIP (Cplex) 2013 Stochastic programming extension of GAMS EMP 2013 GDXRRW interface between GAMS and R 2014 Local search solver LocalSolver added to solver portfolio 2014 End of support for 32 bit Linux and 32 bit Solaris 2015 LaTeX documentation from GAMS source (Model2TeX) 2015 End of support for Win XP 2016 New Management Team 2017 EmbeddedCode Facility 2017 C++ API 2017 Introduction of "Core" and "Peripheral" platforms 2018 GAMS Studio (Beta) 2018 End of support for x86-64 Solaris 2019 GAMS MIRO - Model Interface with Rapid Orchestration (Beta) 2019 End of support for Win7, moved 32 bit Windows to peripheral platforms 2019 Altered versioning scheme to XX.Y.Z 2020 Introduction of demo and community licensing scheme 2020 Official release of GAMS MIRO (Model Interface with Rapid Orchestration) for deployment of GAMS models as interactive applications 2021 Official release of GAMS Engine, the new solution for running GAMS jobs in cloud environments 2022 Official release of GAMS Engine SaaS, the hosted version of GAMS Engine Background The driving force 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