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 Recent developments in (Global) Optimization are surveyed in this paper. We
collected and commented quite a large number of recent references which, in our opinion …

Within state-of-the-art solvers such as IBM-CPLEX, the ability to solve both convex and
nonconvex Mixed-Integer Quadratic Programming (MIQP) problems to proven optimality …

First-order methods for quadratic optimization such as OSQP are widely used for large-scale
machine learning and embedded optimal control, where many related problems must be …

The maximum-cut problem is one of the fundamental problems in combinatorial
optimization. With the advent of quantum computers, both the maximum-cut and the …

This book arose from a realization that modeling using mathematical programming should
be tightly linked with algorithms and their software implementation to solve optimization …

Solving optimization problems is challenging for existing digital computers and even for
future quantum hardware. The practical importance of diverse problems, from healthcare to …

We present a novel branch-and-bound solver for mixed-integer quadratic programs (MIQPs)
that efficiently exploits the first-order OSQP solver for the quadratic program (QP) sub …

Gradient descent is a fundamental algorithm in both theory and practice for continuous
optimization. Identifying its quantum counterpart would be appealing to both theoretical and …

We propose an efficient algorithm that combines column generation and quantum annealing
to solve binary quadratic problems. Binary quadratic problems are difficult to solve because …