3 papers
math.OC2026
Learning-Augmented Optimization for Strategic Two-Echelon Spare Parts Network Design
Donato Maragno, Marco Caserta, Alberto Sinigaglia +3
We study the strategic design of a two-echelon spare-parts inventory network where evaluating each candidate topology requires an expensive inventory optimization model. The design…
cs.LG2024
Output-Constrained Decision Trees
Hüseyin Tunç, Doğanay Özese, Ş. İlker Birbil +3
Incorporating domain-specific constraints into machine learning models is essential for generating predictions that are both accurate and feasible in real-world applications. This…
cs.LG2024
Large Scale Constrained Clustering With Reinforcement Learning
Benedikt Schesch, Marco Caserta
Given a network, allocating resources at clusters level, rather than at each node, enhances efficiency in resource allocation and usage. In this paper, we study the problem of find…