GAPSPLIT: Efficient random sampling for non-convex constraint-based models

Abstract

GAPSPLIT generates random samples from convex and non-convex constraint-based models by targeting under-sampled regions of the solution space. GAPSPLIT provides uniform coverage of linear, mixed-integer and general non-linear models.