A Penalty Branch-and-Bound Method for Mixed-Binary Linear Complementarity Problems

Linear complementarity problems (LCPs) are an important modeling tool for many practically relevant situations but also have many important applications in mathematics itself. Although the continuous version of the problem is extremely well studied, much less is known about mixed-integer LCPs (MILCPs) in which some variables have to be integer-valued in a solution. In particular, … Read more

Limit sets in global multiobjective optimization

Inspired by the recently introduced branch-and-bound method for continuous multiobjective optimization problems from G. Eichfelder, P. Kirst, L. Meng, O. Stein, A general branch-and-bound framework for continuous global multiobjective optimization, Journal of Global Optimization, 80 (2021) 195-227, we study for a general class of branch-and-bound methods in which sense the generated terminal enclosure and the … Read more

Lower Bounds on the Size of General Branch-and-Bound Trees

A \emph{general branch-and-bound tree} is a branch-and-bound tree which is allowed to use general disjunctions of the form $\pi^{\top} x \leq \pi_0 \,\vee\, \pi^{\top}x \geq \pi_0 + 1$, where $\pi$ is an integer vector and $\pi_0$ is an integer scalar, to create child nodes. We construct a packing instance, a set covering instance, and a … Read more

A Survey on Mixed-Integer Programming Techniques in Bilevel Optimization

Bilevel optimization is a field of mathematical programming in which some variables are constrained to be the solution of another optimization problem. As a consequence, bilevel optimization is able to model hierarchical decision processes. This is appealing for modeling real-world problems, but it also makes the resulting optimization models hard to solve in theory and … Read more

On the Integrality Gap of Binary Integer Programs with Gaussian Data

For a binary integer program (IP) $\max c^\T x, Ax \leq b, x \in \{0,1\}^n$, where $A \in \R^{m \times n}$ and $c \in \R^n$ have independent Gaussian entries and the right-hand side $b \in \R^m$ satisfies that its negative coordinates have $\ell_2$ norm at most $n/10$, we prove that the gap between the value … Read more

Branch-and-Bound Solves Random Binary IPs in Polytime

Branch-and-bound is the workhorse of all state-of-the-art mixed integer linear programming (MILP) solvers. These implementations of branch-and-bound typically use variable branching, that is, the child nodes are obtained by fixing some variable to an integer value v in one node and to v + 1 in the other node. Even though modern MILP solvers are … Read more

Branch-and-Refine for Solving Time-Dependent Problems

One of the standard approaches for solving time-dependent discrete optimization problems, such as the traveling salesman problem with time-windows or the shortest path problem with time-windows, is to derive a so-called time-indexed formulation. If the problem has an underlying structure that can be described by a graph, the time-indexed formulation is usually based on a … Read more

Linearization and Parallelization Schemes for Convex Mixed-Integer Nonlinear Optimization

We develop and test linearization and parallelization schemes for convex mixed-integer nonlinear programming. Several linearization approaches are proposed for LP/NLP based branch-and-bound. Some of these approaches strengthen the linear approximation to nonlinear constraints at the root node and some at the other branch-and-bound nodes. Two of the techniques are specifically applicable to commonly found univariate … Read more

Sparse Regression at Scale: Branch-and-Bound rooted in First-Order Optimization

We consider the least squares regression problem, penalized with a combination of the L0 and L2 norms (a.k.a. L0 L2 regularization). Recent work presents strong evidence that the resulting L0-based estimators can outperform popular sparse learning methods, under many important high-dimensional settings. However, exact computation of L0-based estimators remains a major challenge. Indeed, state-of-the-art mixed … Read more

Complexity of cutting planes and branch-and-bound in mixed-integer optimization

We investigate the theoretical complexity of branch-and-bound (BB) and cutting plane (CP) algorithms for mixed-integer optimization. In particular, we study the relative efficiency of BB and CP, when both are based on the same family of disjunctions. We extend a result of Dash to the nonlinear setting which shows that for convex 0/1 problems, CP … Read more