10 citations · 31 across the 24 of their papers we have counts for
6 papers · 1 filter
Santa Claus meets Makespan and Matroids: Algorithms and Reductions
Étienne Bamas, Alexander Lindermayr, Nicole Megow +2
In this paper we study the relation of two fundamental problems in scheduling and fair allocation: makespan minimization on unrelated parallel machines and max-min fair allocation,…
Recoverable Robust Optimization with Commitment
Felix Hommelsheim, Nicole Megow, Komal Muluk +1
We propose a model for recoverable robust optimization with commitment. Given a combinatorial optimization problem and uncertainty about elements that may fail, we ask for a robust…
Sorting and Hypergraph Orientation under Uncertainty with Predictions
Thomas Erlebach, Murilo Santos de Lima, Nicole Megow +1
Learning-augmented algorithms have been attracting increasing interest, but have only recently been considered in the setting of explorable uncertainty where precise values of unce…
On Solution Discovery via Reconfiguration
Michael R. Fellows, Mario Grobler, Nicole Megow +5
The dynamics of real-world applications and systems require efficient methods for improving infeasible solutions or restoring corrupted ones by making modifications to the current…
Speed-Oblivious Online Scheduling: Knowing (Precise) Speeds is not Necessary
Alexander Lindermayr, Nicole Megow, Martin Rapp
We consider online scheduling on unrelated (heterogeneous) machines in a speed-oblivious setting, where an algorithm is unaware of the exact job-dependent processing speeds. We sho…
Minimalistic Predictions to Schedule Jobs with Online Precedence Constraints
Alexandra Lassota, Alexander Lindermayr, Nicole Megow +1
We consider non-clairvoyant scheduling with online precedence constraints, where an algorithm is oblivious to any job dependencies and learns about a job only if all of its predece…