MINLP formulations for continuous piecewise linear function fitting
指出Goldberg等人提出的分段线性函数拟合MINLP模型因缺少必要约束而可能产生非函数图形，给出反例并提出三种修正模型，比较了它们的理论关系与计算性能。
Abstract We consider a nonconvex mixed-integer nonlinear programming (MINLP) model proposed by Goldberg et al. (Comput Optim Appl 58:523–541, 2014. 10.1007/s10589-014-9647-y ) for piecewise linear function fitting. We show that this MINLP model is incomplete and can result in a piecewise linear curve that is not the graph of a function, because it misses a set of necessary constraints. We provide two counterexamples to illustrate this effect, and propose three alternative models that correct this behavior. We investigate the theoretical relationship between these models and evaluate their computational performance.