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Welcome to the RobustOptimization wiki!

This is a Julia program for introductory (adjustable) robust optimization by matrix computation with box uncertainty and budget of uncertainty.

According to the definition of robust optimization in Wikipedia 1:

Robust optimization is a field of optimization theory that deals with optimization problems in which a certain measure of robustness is sought against uncertainty that can be represented as deterministic variability in the value of the parameters of the problem itself and/or its solution.

To illustrate the importance of robustness in practical applications, we quote from the case study by Ben-Tal and Nemirovski (2000)2 on linear optimization problems from the Net-Lib library 2:

In real-world applications of Linear Programming, one can- not ignore the possibility that a small uncertainty in the data can make the usual optimal solution completely meaningless from a practical viewpoint.