7 citations · 10 across the 4 of their papers we have counts for
4 papers
Combinatorial Optimization and Machine Learning for Dynamic Inventory Routing
Toni Greif, Louis Bouvier, Christoph M. Flath +3
We introduce a combinatorial optimization-enriched machine learning pipeline and a novel learning paradigm to solve inventory routing problems with stochastic demand and dynamic in…
Combinatorial Optimization enriched Machine Learning to solve the Dynamic Vehicle Routing Problem with Time Windows
Léo Baty, Kai Jungel, Patrick S. Klein +2
With the rise of e-commerce and increasing customer requirements, logistics service providers face a new complexity in their daily planning, mainly due to efficiently handling same…
Learning with Combinatorial Optimization Layers: a Probabilistic Approach
Guillaume Dalle, Léo Baty, Louis Bouvier +1
Combinatorial optimization (CO) layers in machine learning (ML) pipelines are a powerful tool to tackle data-driven decision tasks, but they come with two main challenges. First, t…
Stochastic Shortest Paths and Risk Measures
Axel Parmentier, Frédéric Meunier
We consider three shortest path problems in directed graphs with random arc lengths. For the first and the second problems, a risk measure is involved. While the first problem cons…