The selection of branching variables is a key component of branch-and-bound algorithms for
solving mixed-integer programming (MIP) problems since the quality of the selection …

We describe a tabu search (TS) approach for solving general zero-one mixed integer
programming (MIP) problems that exploits the extreme point property of zero-one solutions …

We introduce a prescriptive machine learning approach to speed up the process of solving
mixed-integer convex optimization (MICO) problems. We solve multiple optimization …

MINTO is a software system that solves mixed-integer linear programs by a branch-
andbound algorithm with linear programming relaxations. It also provides automatic …

In contrast to previous competitions, where the problems were goal-based, the 2011
International Probabilistic Planning Competition (IPPC-2011) emphasized finite-horizon …

The availability of effective exact or heuristic solution methods for general Mixed-Integer
Programs (MIPs) is of paramount importance for practical applications. In the present paper …

Conflict-based Search (CBS) is a effective approach to optimal multi-agent path finding.
However, performance of CBS approaches degrade rapidly in highly-contended graphs with …

In cost-optimal planning we aim to find a sequence of operators that achieve a set of goals
with minimum cost. Symbolic search with Binary Decision Diagrams (BDDs) performs …

This paper studies how to design abstractions of large-scale combinatorial optimization
problems that can leverage existing state-of-the-art solvers in general-purpose ways, and …

Algorithm portfolio and selection approaches have achieved remarkable improvements over
single solvers. However, the implementation of such systems is often highly customised and …