The SCIP Optimization Suite provides a collection of software packages for mathematical
optimization centered around the constraint integer programming framework SCIP. This …

JuMP is an open-source modeling language that allows users to express a wide range of
optimization problems (linear, mixed-integer, quadratic, conic-quadratic, semidefinite, and …

We consider the least squares regression problem, penalized with a combination of the ℓ _ 0
ℓ 0 and squared ℓ _ 2 ℓ 2 penalty functions (aka ℓ _0 ℓ _2 ℓ 0 ℓ 2 regularization). Recent …

We study a seemingly unexpected and relatively less understood overfitting aspect of a
fundamental tool in sparse linear modeling—best subset selection—which minimizes the …

We consider a family of competitive facility location problems in which a “newcomer”
company enters the market and has to decide where to locate a set of new facilities so as to …

The everlasting consumption of fossil fuels with limited reserves amid climate change and
environmental pollution arises public awareness of sustainable development, which calls for …

A mixed-integer convex (MI-convex) optimization problem is one that becomes convex when
all integrality constraints are relaxed. We present a branch-and-bound LP outer …

The sparse portfolio selection problem is one of the most famous and frequently studied
problems in the optimization and financial economics literatures. In a universe of risky …

Tree ensembles can be well-suited for black-box optimization tasks such as algorithm tuning
and neural architecture search, as they achieve good predictive performance with little or no …

Signal estimation problems with smoothness and sparsity priors can be naturally modeled
as quadratic optimization with ℓ0-" norm" constraints. Since such problems are nonconvex …