RSOME in Python: An Open-Source Package for Robust Stochastic Optimization Made Easy

We introduce a Python package called RSOME for modeling a wide spectrum of robust and distributionally robust optimization problems. RSOME serves as an open-source framework for modeling various optimization problems subject to distributional ambiguity in a highly readable and mathematically intuitive manner. It is versatile and fits well in the open-source software community in the sense that (i) it is consistent with NumPy arrays in indexing and slicing and; (ii) together with the rich Python libraries for machine learning, data analysis, and visualization, it is easy to implement data-driven models; and (iii) it provides convenient interfaces for users to switch and tune parameters among different solvers.

Automated summary

RSOME is a Python package that models a wide range of robust and distributionally robust optimization problems. It provides an open-source framework for modeling optimization problems with distributional ambiguity in a readable and intuitive manner. It is versatile, compatible with NumPy arrays for indexing and slicing, easily implements data-driven models with Python libraries, and offers convenient interfaces for users to switch and tune parameters among different solvers.