Modeling disjunctive constraints with a logarithmic number of binary variables and constraints

By Juan Pablo Vielma, George L. Nemhauser. Mathematical programming, 2008

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Mixed-Integer Models for Nonseparable Piecewise-Linear Optimization: Unifying Framework and Extensions (2010, methodology): “Figure 2 Examples of triangulations of subsets of R 2 . and Vielma and Nemhauser (2008b) for the case when the family of polytopes P is topologically equivalent or compatible (Aichholzer et al. 2003) with a triangulation known as J 1 or " Union Jack " (Todd 1977).”
A Review of Piecewise Linearization Methods (2013, methodology): “Vielma and Nemhauser [50] recently developed a novel piecewise linear expression requiring fewer variables and constraints than the current piecewise linearization techniques to approximate the univariate nonlinear functions.”
Gas Network Optimization: A comparison of Piecewise Linear Models (2014, methodology): “For more details about how to construct261 injective functions see Vielma and Nemhauser (2011) and Geißler et al. (2012).262 3.2.”
Strong mixed-integer programming formulations for trained neural networks (2018, background): “is an ideal extended formulation for piecewise linear functions [52].”