COIN-OR was founded in 2000 with the mission to create and disseminate knowledge related to all aspects of computational operations research. Since it's founding, COIN-OR has been successful in publishing dozens of state-of-the-art optimization solvers under open source licenses. COIN-OR projects, such as Cbc, Clp, Ipopt, and Pyomo, are now used by thousands of organizations around the world. Additionally, new projects have demonstrated great potential. Gravity, an algebraic modeling language written in C++, was used by the winning team of the recent ARPA-E Grid Optimization Competition, and the authors of Gravity were awarded the COIN-OR Cup for 2021. COIN-OR’s solvers are ubiquitous in both open source software and industry, and are currently packaged in most major Linux distributions, homebrew core (Mac OS X), vcpkg, conan, conda, and with interfaces in Python, Julia, Matlab, R, sage, and many other environments.

Despite widespread usage, there has been effectively no direct funding going to COIN-OR in recent years to foster the sustainability of the projects it hosts. Many of the original developers have moved on and we are struggling to maintain an ever-increasing code base. Finally, the core contributor pool largely consists of academics who simply lack the bandwidth to both publish research and continue ensuring the usability, reliability and security of the software they produce.

However, we are optimistic about the future! We know that we have a wonderful community of users who we know are supportive of our efforts. What we need is a sustainable stream of funding. The goal of this fundraising will be to create 1-2 part-time paid positions whose focus will be:

1. Increasing contributor diversity by making it easier for non-academic contributors to get involved with COIN-OR.
2. Increasing usability by paying down the technical debt related to documentation, compilation, security, tests and releases
3. Engaging with existing users who have previously opened issues or sent pull requests to identify and address common classes of issues, refine workflows, and implement open source best practices

We hope that by securing funding for some temporary, paid contributors, we will be able to adopt long-term sustainable strategies for growing the COIN-OR community, improve the user experience of our open source solvers, and speed up our release cycles to more quickly bring the latest optimization research to the general public.

For more context about our search for funding and the future of COIN-OR, refer to our recent blog post.