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Explore a 13-minute video presentation on LoReSIO.jl, a package that extends JuMP to implement innovative optimization techniques for solving nonlinear and non-convex semi-infinite optimization programs (SIPs). Learn how this package tackles problems with finite variables but infinite constraints by employing local reduction methods to replace infinite constraints with an optimally chosen finite scenario set. Discover how LoReSIO.jl enables faster solutions for robust control and min-max problems compared to direct implementations of global solution methods, while using fewer samples than scenario tree approaches. Understand the package's compatibility with most JuMP-supported solvers, allowing users to utilize dedicated linear or quadratic solvers for simpler problems and more general nonlinear solvers for complex ones. Gain insights into quickly defining SIPs within LoReSIO.jl and examine examples of discrete-time robust optimal control, showcasing the range of solvable problems and the achievable numerical speedups.
