Published in Ecole doctorale des sciences des métiers et de l'ingénieur, 2026
PhD dissertation
Recommended citation: Strang, P. (2026). Learning to solve repeated combinatorial optimization problems exactly (Doctoral dissertation, HESAM Université).
Published in AAAI Conference on Artificial Intelligence (AAAI), 2026
We introduce PlanB&B, a model-based reinforcement learning agent that learns an internal model of Branch & Bound dynamics to derive improved branching strategies for variable selection in B&B.
Recommended citation: Strang, P., Alès, Z., Bissuel, C., Juan, O., Kedad-Sidhoum, S., Rachelson, E., (2026). Planning in Branch-and-Bound: Model-based Reinforcement Learning for Exact Combinatorial Optimization. Proceedings of the Fortieth AAAI Conference on Artificial Intelligence..
Published in Neural Information Processing Systems (NeurIPS), 2025
In this work, we introduce BBMDP, a principled vanilla MDP formulation for variable selection in B&B, allowing to leverage a broad range of RL algorithms for the purpose of learning optimal B&B heuristics.
Recommended citation: Strang, P., Ales, Z., Bissuel, C., Juan, O., Kedad-Sidhoum, S., Rachelson, E., 2025. A Markov Decision Process for Variable Selection in Branch & Bound. Presented at the The Thirty-ninth Annual Conference on Neural Information Processing Systems.
Published in MIP Workshop, 2023
On the occasion of the 20th Mixed Integer Program Workshop Computational Competition, this work introduces a new approach for learning to solve MIPs online.
Recommended citation: Strang, P., Alès, Z., Bissuel, C., Juan, O., Kedad-Sidhoum, S., Rachelson, E., (2023). Influence branching for learning to solve mixed-integer programs online. Mixed Integer Programming Workshop.