5 papers
CG4AI: A Column Generation Framework for Training AI Models Under Constraints
Youcef Magnouche, Abderrahmane Driouch, Sébastien Martin +1
Standard machine-learning training minimizes a loss function over a dataset, but does not guarantee that the resulting model will satisfy predefined rules or constraints on its out…
On the Multi-Commodity Flow with convex objective function: Column-Generation approaches
Guillaume Beraud-Sudreau, Lucas Létocart, Youcef Magnouche +1
The purpose of this work is to develop an algorithmic optimization approach for a capacitated Multi-Commodity flow problem, where the objective is to minimize the total link costs,…
Atomic Column Generation For Consensus Between Algorithms: Application to Path Computation
Sébastien Martin, Pierre Bauguion, Youcef Magnouche +1
In real-life applications, most optimization problems are variants of well-known combinatorial optimization problems, including additional constraints to fit with a particular use…
Alternative paths computation for congestion mitigation in segment-routing networks
Sébastien Martin, Youcef Magnouche, Paolo Medagliani +1
In backbone networks, it is fundamental to quickly protect traffic against any unexpected event, such as failures or congestions, which may impact Quality of Service (QoS). Standar…
Protected load balancing problem: Neural-network based approximation for non-convex optimization
Youcef Magnouche, Sébastien Martin, Jérémie Leguay
Nowadays, centralized Path Computation Elements (PCE) integrate control plane algorithms to optimize routing and load-balancing continuously. When a link fails, the traffic load is…