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Explore a 12-minute video introducing PiecewiseAffineApprox.jl, a Julia package designed for automatic computation of piecewise affine convex (concave) approximations in optimization models. Learn how this tool, based on JuMP, simplifies the development of optimization models incorporating nonlinear expressions, particularly those derived from measurements or simulations. Discover the package's API features, including options for best fit, over- or under-estimation, various error measures, and integration with JuMP models. Understand the two methods provided for calculating optimal approximations: a heuristic search based on Magnani & Boyd's work and an optimization approach inspired by Toriello & Vielma's research. Gain insights into the package's practical application through an energy-related use case demonstration. Note that the package is scheduled for public release in spring 2024.
