UvA-DARE (Digital Academic Repository) Mixed-Integer Optimization with Constraint Learning
This work proposes an end-to-end pipeline for data-driven decision making in which constraints and objectives are directly learned from data using machine learning, and the trained models are embedded in an optimization formulation.
Donato Maragno, H. Wiberg, D. Bertsimas et al.
· 0 citations