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.
NomadBBO is presented, a user-friendly Python library for inequality-constrained mixed-variable blackbox optimization built around Nomad, a new direct-search method that extends Adaptive Direct Search to mixed-variable problems.
Self-supervised learning for combinatorial optimization has emerged as a promising paradigm for solving discrete optimization problems with neural networks, but a central challenge remains: handling hard combinatorial constraints within continuous, gradient-based training. Continuously extending combinatorial objective...
Akbar Rafiey, Yi-Fei Xu, Nikolaos Karalias· 0 citations
In this work, we consider decision-focused learning (DFL) for a Markov decision process (MDP), where existing methods differentiate through the KKT conditions of the Bellman equation and require solving a linear system over all state-action pairs, limiting its scalability. We address this by reformulating the MDP as an...
Zi-Hao Zhao, Ashwath K. Karunakaram, A. Eshragh et al.· 0 citations
This work proposes CG4AI, a framework that builds a convex combination of AI models while enforcing linear constraints on the combined output, and applies it to digit classification on MNIST and the multi-commodity flow problem, where link capacity constraints are enforced on neural-network routing predictors.
Youcef Magnouche, Abderrahmane Driouch, Sébastien Martin et al.· 0 citations
This work presents a new approach that leverages a multitask GP model to jointly learn all objectives and constraints, and proposes a total correlation metric that enables identifying an ${optimal}$ subset of objectives and constraints to be evaluated at every round, even under uniform evaluation costs.
A unified framework, based on decision diagrams, is proposed that serves both to solve the associated optimization problems and to construct ideal conic quadratic extended formulations of the closure of the convex hull of the underlying mixed-integer set.
Soobin Choi, S. Fattahi, Andrés Gómez et al.· 1 citation
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