1 citations · 1 across the 4 of their papers we have counts for
4 papers
Multi-Action Self-Improvement for Neural Combinatorial Optimization
Laurin Luttmann, Lin Xie
Self-improvement has emerged as a state-of-the-art paradigm in Neural Combinatorial Optimization (NCO), where models iteratively refine their policies by generating and imitating h…
Learning to Solve the Min-Max Mixed-Shelves Picker-Routing Problem via Hierarchical and Parallel Decoding
Laurin Luttmann, Lin Xie
The Mixed-Shelves Picker Routing Problem (MSPRP) is a fundamental challenge in warehouse logistics, where pickers must navigate a mixed-shelves environment to retrieve SKUs efficie…
PARCO: Parallel AutoRegressive Models for Multi-Agent Combinatorial Optimization
Federico Berto, Chuanbo Hua, Laurin Luttmann +6
Combinatorial optimization problems involving multiple agents are notoriously challenging due to their NP-hard nature and the necessity for effective agent coordination. Despite ad…
Formulating and solving integrated order batching and routing in multi-depot AGV-assisted mixed-shelves warehouses
Lin Xie, Hanyi Li, Laurin Luttmann
Different retail and e-commerce companies are facing the challenge of assembling large numbers of time-critical picking orders that include both small-line and multi-line orders. T…