ROC++ is a C++ based platform for modeling, automatically reformulating, and solving robust optimization problems. ROC++ can address both single- and multi-stage problems involving exogenous and/or endogenous uncertain parameters and real- and/or binary-valued adaptive variables. The ROC++ modeling language is similar to the one provided for the deterministic case by state-of-the-art deterministic optimization solvers. ROC++ comes with detailed documentation to facilitate its use and expansion. It is open-source for educational, research, and non-profit purposes.
Check-out the ROC++ homepage to download the latest version and to find out more: https://sites.google.com/usc.edu/robust-opt-cpp/home
ROC++: Robust Optimization in C++
P. Vayanos, Q. Jin, and G. Elissaios
Technical Report, University of Southern California, June 2020, available on Optimization Online.
National Science Foundation, Operations Engineering
Role: PI (with Co-PI: B. Dilkina)
Award #: OE-1763108
Total Award Period Covered: 07/15/2018-07/14/2022 (4 Years)
Total Award Amount: $535,335
Own Share: $403,638