Robust optimization via randomized algorithms

This paper gives an overview on probabilistic approach to robust optimization and chance constrained optimization. The problems are to minimize a linear objective function subject to a parameter dependent convex constraint, where a probability measure is introduced onto the parameter set. Two randomized techniques, the scenario optimization and the sequential optimization, are summarized, where characteristics and advantages of both techniques are discussed.