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Research

Our innovations are built on a foundation of top-tier research spanning Operations Research and Machine Learning. By uniting advanced optimization methods with state-of-the-art predictive modeling, our work tackles some of the most complex challenges in industry today. This rigorous scientific approach not only drives our publications in leading journals and conferences but also ensures that our solutions are both theoretically robust and practically transformative. It is this deep connection to cutting-edge research that allows us to continuously push the boundaries of what’s possible in decision-making.

Selected Awards

Selected Publications

The publications below are co-authored by our founders, and focus on the core scientific foundations of Praedon solutions.

Article

2025

Staggered routing in autonomous mobility-on-demand systems

European Journal of Operational Research

A. Coppola, G. Hiermann, D. Paccagnan, and Maximilian Schiffer

Preprint

2025

Primal-dual algorithm for contextual stochastic combinatorial optimization

Preprint

Louis Bouvier, Thibault Prunet, Vincent Leclère, and Axel Parmentier

Article

2025

Learning-Based Online Optimization for Autonomous Mobility-on-Demand Fleet Control

INFORMS Journal on Computing

Kai Jungel, Axel Parmentier, Maximilian Schiffer, and Thibaut Vidal

Preprint

2025

Preference-Aware Compensation Policies for Crowdsourced on-Demand Services

Preprint

Georgina Nouli, Axel Parmentier, and Maximilian Schiffer

Preprint

2025

Learning with Local Search MCMC Layers

Preprint

Germain Vivier-Ardisson, Mathieu Blondel, and Axel Parmentier

Preprint

2025

Optimizing a Worldwide-Scale Shipper Transportation Planning in a Carmaker Inbound Supply Chain

Preprint

Mathis Brichet, Maximilian Schiffer, and Axel Parmentier

Article

2025

Learning Structured Approximations of Combinatorial Optimization Problems

Open Journal Of Mathematical Optimization, in press

Axel Parmentier

Preprint

2025

Aircraft routing: periodicity and complexity

Preprint

Frédéric Meunier, Axel Parmentier, and Nour ElHouda Tellache

Preprint

2025

Structured Reinforcement Learning for Combinatorial Decision-Making

Preprint

Heiko Hoppe, Léo Baty, Louis Bouvier, Axel Parmentier, and Maximilian Schiffer

Article

2025

Support vector machines with the hard-margin loss: optimal training via combinatorial Benders' cuts

Journal of Global Optimization

Ítalo Santana, Breno Serrano, Maximilian Schiffer, and Thibaut Vidal

Article

2024

Solving a Continent-Scale Inventory Routing Problem at Renault

Transportation Science

Louis Bouvier, Guillaume Dalle, Axel Parmentier, and Thibaut Vidal

Article

2024

Linear Lexicographic Optimization and Preferential Bidding System

Transportation Science

Nour ElHouda Tellache, Frédéric Meunier, and Axel Parmentier

conference

2024

WardropNet: Traffic Flow Predictions via Equilibrium-Augmented Learning

ICML

Kai Jungel, Dario Paccagnan, Axel Parmentier, Maximilian Schiffer

Proceedings

2024

Predicting Accurate Lagrangian Multipliers for Mixed Integer Linear Programs

Accepted at the 41st International Conference on Machine Learning

Francesco Demelas, Joseph Le Roux, Mathieu Lacroix, and Axel Parmentier

Proceedings

2024

DistrictNet: Decision-aware Learning for Geographical Districting

The Thirty-eighth Annual Conference on Neural Information Processing Systems

Cheikh Ahmed, Alexandre Forel, Axel Parmentier, and Thibaut Vidal

Proceedings

2024

Don't Explain Noise: Robust Counterfactuals for Randomized Ensembles

Proceedings of 21st International Conference on the Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming (CPAIOR 2024)

Alexandre Forel, Axel Parmentier, and Thibaut Vidal

Proceedings

2024

CF-OPT: Counterfactual Explanations for Structured Prediction

Accepted at the 41st International Conference on Machine Learning

Germain Vivier-Ardisson, Alexandre Forel, Axel Parmentier, and Thibaut Vidal

Article

2024

Combinatorial Optimization-Enriched Machine Learning to Solve the Dynamic Vehicle Routing Problem with Time Windows

Transportation Science

Léo Baty, Kai Jungel, Patrick S. Klein, Axel Parmentier, and Maximilian Schiffer

Proceedings

2024

Dynamic Neighborhood Construction for Structured Large Discrete Action Spaces

The Twelfth International Conference on Learning Representations (ICLR)

F. Akkerman, J. Luy, W. van Heeswijk, and Maximilian Schiffer

Article

2024

Bilevel optimization for feature selection in the data-driven newsvendor problem

European Journal of Operational Research

B. Serrano, S. Minner, Maximilian Schiffer, and T. Vidal

Preprint

2024

Generalization Bounds of Surrogate Policies for Combinatorial Optimization Problems

Preprint

Pierre-Cyril Aubin-Frankowski, Yohann De Castro, Axel Parmentier, and Alessandro Rudi

Preprint

2024

Combinatorial Optimization and Machine Learning for Dynamic Inventory Routing

Preprint

Toni Greif, Louis Bouvier, Christoph M. Flath, Axel Parmentier, Sonja U. K. Rohmer, and Thibaut Vidal

Proceedings

2024

Global rewards in multi-agent deep reinforcement learning for autonomous mobility on demand systems

6th Annual Learning for Dynamics & Control Conference

H. Hoppe, T. Enders, Q. Cappart, and Maximilian Schiffer

journal

2023

Electric Vehicle Fleets: Scalable Route and Recharge Scheduling through Column Generation

Naval Research Logistics

Axel Parmentier, Rafael Martinelli, Thibaut Vidal

Article

2023

Future Memories Are Not Needed for Large Classes of POMDPs

Operations Research Letters

Victor Cohen, and Axel Parmentier

Proceedings

2023

Hybrid Multi-Agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems

5th Annual Conference on Learning for Dynamics and Control

T. Enders, J. Harrison, M. Pavone, and Maximilian Schiffer

Proceedings

2023

Optimal Decision Diagrams for Classification

AAAI Conference on Artificial Intelligence

A. Florio, P. Martins, Maximilian Schiffer, T. Serra, and T. Vidal

Proceedings

2023

Explainable Data-Driven Optimization: From Context to Decision and Back Again

Proceedings of the 40th International Conference on Machine Learning

Alexandre Forel, Axel Parmentier, and Thibaut Vidal

Preprint

2022

Learning with Combinatorial Optimization Layers: A Probabilistic Approach

Preprint

Guillaume Dalle, Léo Baty, Louis Bouvier, and Axel Parmentier

Article

2022

Structured Learning Based Heuristics to Solve the Single Machine Scheduling Problem with Release Times and Sum of Completion Times

European Journal of Operational Research

Axel Parmentier, and Vincent T'Kindt

Article

2021

Learning to Approximate Industrial Problems by Operations Research Classic Problems

Operations Research

Axel Parmentier

conference

2021

Optimal Counterfactual Explanations in Tree Ensembles

ICML

Axel Parmentier, Thibaut Vidal

Article

2020

Integer Programming on the Junction Tree Polytope for Influence Diagrams

INFORMS Journal on Optimization

Axel Parmentier, Victor Cohen, Vincent Leclère, Guillaume Obozinski, and Joseph Salmon

Proceedings

2020

Born-Again Tree Ensembles

International Conference on Machine Learning (ICML)

T. Vidal and Maximilian Schiffer

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