18 citations · 30 across the 7 of their papers we have counts for
7 papers
Learning optimal objective values for MILP
Lara Scavuzzo, Karen Aardal, Neil Yorke-Smith
Modern Mixed Integer Linear Programming (MILP) solvers use the Branch-and-Bound algorithm together with a plethora of auxiliary components that speed up the search. In recent years…
Machine Learning Augmented Branch and Bound for Mixed Integer Linear Programming
Lara Scavuzzo, Karen Aardal, Andrea Lodi +1
Mixed Integer Linear Programming (MILP) is a pillar of mathematical optimization that offers a powerful modeling language for a wide range of applications. During the past decades,…
Learning to branch with Tree MDPs
Lara Scavuzzo, Feng Yang Chen, Didier Chételat +4
State-of-the-art Mixed Integer Linear Program (MILP) solvers combine systematic tree search with a plethora of hard-coded heuristics, such as the branching rule. The idea of learni…
A polynomial size model with implicit SWAP gate counting for exact qubit reordering
Jesse Mulderij, Karen I. Aardal, Irina Chiscop +1
Due to the physics behind quantum computing, quantum circuit designers must adhere to the constraints posed by the limited interaction distance of qubits. Existing circuits need th…
Approximation algorithms for the Transportation Problem with Market Choice and related models
Karen Aardal, Pierre Le Bodic
Given facilities with capacities and clients with penalties and demands, the transportation problem with market choice consists in finding the minimum-cost way to partition the cli…
Approximation Algorithms for Hard Capacitated -facility Location Problems
Karen Aardal, Pieter van den Berg, Dion Gijswijt +1
We study the capacitated -facility location problem, in which we are given a set of clients with demands, a set of facilities with capacities and a constant number . It costs…
An optimal bifactor approximation algorithm for the metric uncapacitated facility location problem
Jaroslaw Byrka, Karen Aardal
We obtain a 1.5-approximation algorithm for the metric uncapacitated facility location problem (UFL), which improves on the previously best known 1.52-approximation algorithm by Ma…