Publications and responsibilities
Combinatorial Learning in Traffic Management
Inventory Management under Storage and Order Restrictions
The landscape of quantum algorithms
An Exact Algorithm for Robust Influence Maximization
MILP approaches to practical real-time train scheduling: the Iron Ore Line case
A novel formulation for job-shop scheduling in traffic management
A central problem in traffic management is that of scheduling the movements of vehicles so as to minimize the cost of the schedule. This problem can be modeled as a job-shop scheduling problem. We present a new MILP formulation which is alternative to classical approaches such as big-M and time...
The Path&Cycle formulation for the Hotspot Problem in Air Traffic Management
The Hotspot Problem in Air Traffic Management consists of optimally rescheduling a set of airplanes that are forecast to occupy an overcrowded region of the airspace, should they follow their original schedule. We first provide a MILP model for the Hotspot Problem using a standard big-M formulation....
Hotspot Resolution with Sliding Window Capacity Constraints using the Path&Cycle Algorithm
We extend the new, efficient Path&Cycle formulation for the Hotspot Problem with two methods for dealing with windowed capacity constraints. We also discuss how to combine constraints to allow two-level capacity restricions for peak and average load respectively. Finally, we present computationa...