Many traditional algorithms for solving combinatorial optimization problems involve using
hand-crafted heuristics that sequentially construct a solution. Such heuristics are designed …

In this paper, we present a review of deterministic software for solving convex MINLP
problems as well as a comprehensive comparison of a large selection of commonly …

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

Combinatorial optimization problems are typically tackled by the branch-and-bound
paradigm. We propose a new graph convolutional neural network model for learning branch …

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

Electric vehicles (EVs) have been popularly adopted and deployed over the past few years
because they are environment-friendly. When integrated into smart grids, EVs can operate …

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

We report on the selection process leading to the sixth version of the Mixed Integer
Programming Library, MIPLIB 2017. Selected from an initial pool of 5721 instances, the new …

Abstract A recent Graph Neural Network (GNN) approach for learning to branch has been
shown to successfully reduce the running time of branch-and-bound algorithms for Mixed …

Energy is a vital resource for human activities and lifestyle, powering important everyday
infrastructures and services. Currently, pollutant and non-renewable sources, such as fossil …