9 papers
Dynamic capacity allocation of hybrid transportation units for cargo-hitching in urban public transportation systems
Paul Bischoff, Benedikt Lienkamp, Tarun Rambha +1
To improve the utilization of public transportation systems (PTSs) during off-peak hours, we present an algorithmic framework that designs PTSs with hybrid transportation units (HT…
Neural Cluster First, Route Second: One-Shot Capacitated Vehicle Routing via Differentiable Optimal Transport
Samuel J. K. Chin, Maximilian Schiffer
The Capacitated Vehicle Routing Problem (CVRP) underpins modern last-mile logistics. Current Neural Combinatorial Optimization (NCO) methods construct CVRP solutions autoregressive…
Breaking the Grid: Distance-Guided Reinforcement Learning in Large Discrete Action Spaces
Heiko Hoppe, Fabian Akkerman, Wouter van Heeswijk +1
Reinforcement Learning (RL) is increasingly applied to large-scale decision-making problems like logistics, scheduling, and recommender systems, but existing algorithms struggle wi…
Linear Decision Tree Policies for Integer Linear Programs
Théo Guyard, Cleber Oliveira, Maximilian Schiffer +2
We study optimal decision policies, represented as linear decision trees, for integer linear programs with a fixed feasible set and varying cost vectors. Once synthesized for a giv…
Optimizing a Worldwide-Scale Shipper Transportation Planning in a Carmaker Inbound Supply Chain
Mathis Brichet, Maximilian Schiffer, Axel Parmentier
We study the shipper-side design of large-scale inbound transportation networks, motivated by the global supply chain of the carmaker Renault. We formalize the Shipper Transportati…
Combinatorial Optimization Augmented Machine Learning
Maximilian Schiffer, Heiko Hoppe, Yue Su +2
Combinatorial optimization augmented machine learning (COAML) has recently emerged as a powerful paradigm for integrating predictive models with combinatorial decision-making. By e…