Copertina

Optimization Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Van Hentenryck, Pascal
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Optimization and Control Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

AI4OPT: AI Institute for Advances in Optimization
di: Van Hentenryck, Pascal, et al.
Pubblicazione: (2023)

Differentiable Optimization for Deep Learning-Enhanced DC Approximation of AC Optimal Power Flow
di: Rosemberg, Andrew, et al.
Pubblicazione: (2025)

Compact Optimality Verification for Optimization Proxies
di: Chen, Wenbo, et al.
Pubblicazione: (2024)

Self-Certifying Primal-Dual Optimization Proxies for Large-Scale Batch Economic Dispatch
di: Klamkin, Michael, et al.
Pubblicazione: (2025)

PGLearn -- An Open-Source Learning Toolkit for Optimal Power Flow
di: Klamkin, Michael, et al.
Pubblicazione: (2025)

Democratizing Large-Scale Re-Optimization with LLM-Guided Model Patches
di: Ye, Tinghan, et al.
Pubblicazione: (2026)

Integrating Column Generation and Large Neighborhood Search for Bus Driver Scheduling with Complex Break Constraints
di: Kletzander, Lucas, et al.
Pubblicazione: (2025)

DualSchool: How Reliable are LLMs for Optimization Education?
di: Klamkin, Michael, et al.
Pubblicazione: (2025)

SPOT: Spatio-Temporal Pattern Mining and Optimization for Load Consolidation in Freight Transportation Networks
di: Cheng, Sikai, et al.
Pubblicazione: (2025)

Bucketized Active Sampling for Learning ACOPF
di: Klamkin, Michael, et al.
Pubblicazione: (2022)

Constraint Programming Models For Serial Batch Scheduling With Minimum Batch Size
di: Huertas, Jorge A., et al.
Pubblicazione: (2025)

Dual Lagrangian Learning for Conic Optimization
di: Tanneau, Mathieu, et al.
Pubblicazione: (2024)

Uncertainty-Aware Delivery Delay Duration Prediction via Multi-Task Deep Learning
di: Faulkner, Stefan, et al.
Pubblicazione: (2026)

Dual Interior Point Optimization Learning
di: Klamkin, Michael, et al.
Pubblicazione: (2024)

Bilevel Optimization and Heuristic Algorithms for Integrating Latent Demand into the Design of Large-Scale Transit Systems
di: Guan, Hongzhao, et al.
Pubblicazione: (2022)

Self-Supervised Learning for Large-Scale Preventive Security Constrained DC Optimal Power Flow
di: Park, Seonho, et al.
Pubblicazione: (2023)

BONO-Bench: A Comprehensive Test Suite for Bi-objective Numerical Optimization with Traceable Pareto Sets
di: Schäpermeier, Lennart, et al.
Pubblicazione: (2026)

R2 v2: The Pareto-compliant R2 Indicator for Better Benchmarking in Bi-objective Optimization
di: Schäpermeier, Lennart, et al.
Pubblicazione: (2024)

Transit Network Design with Two-Level Demand Uncertainties: A Machine Learning and Contextual Stochastic Optimization Framework
di: Guan, Hongzhao, et al.
Pubblicazione: (2026)

Parallel Batch Scheduling With Incompatible Job Families Via Constraint Programming
di: Huertas, Jorge A., et al.
Pubblicazione: (2024)

Practice-Based Optimization for the Strategic Locomotive Assignment Problem
di: Kim, Yunji, et al.
Pubblicazione: (2025)

Paratransit Optimization with Constraint Programming: A Case Study in Savannah, Georgia
di: Jagrowski, Liam, et al.
Pubblicazione: (2025)

Route Optimization Over Scheduled Services For Large-Scale Package Delivery Networks
di: Ahmed, Mohammed Faisal, et al.
Pubblicazione: (2025)

Optimizing Autonomous Transfer Hub Networks: Quantifying the Potential Impact of Self-Driving Trucks
di: Lee, Chungjae, et al.
Pubblicazione: (2023)

Contextual Stochastic Optimization for Omnichannel Multi-Courier Order Fulfillment Under Delivery Time Uncertainty
di: Ye, Tinghan, et al.
Pubblicazione: (2024)

Volt/VAR Optimization in Transmission Networks with Discrete-Control Devices
di: Tong, Shuaicheng, et al.
Pubblicazione: (2026)

Path-Based Formulations for the Design of On-demand Multimodal Transit Systems with Adoption Awareness
di: Guan, Hongzhao, et al.
Pubblicazione: (2023)

On the Viability of Stochastic Economic Dispatch for Real-Time Energy Market Clearing
di: Zhao, Haoruo, et al.
Pubblicazione: (2023)

ODE-based Learning to Optimize
di: Xie, Zhonglin, et al.
Pubblicazione: (2024)

Privacy-Preserving Convex Optimization: When Differential Privacy Meets Stochastic Programming
di: Dvorkin, Vladimir, et al.
Pubblicazione: (2022)

Optimizing Multiple-Control Toffoli Quantum Circuit Design with Constraint Programming
di: Jung, Jihye, et al.
Pubblicazione: (2024)

BenLOC: A Benchmark for Learning to Configure MIP Optimizers
di: Li, Hongpei, et al.
Pubblicazione: (2025)

Scheduling and Routing in the Flexible Job Shop with Heterogeneous Transbots and Zoning: A Constraint Programming Approach
di: Moinuddin, Arnovi, et al.
Pubblicazione: (2026)

Dual Conic Proxy for Semidefinite Relaxation of AC Optimal Power Flow
di: Qiu, Guancheng, et al.
Pubblicazione: (2025)

Halfway Escape Optimization: A Quantum-Inspired Solution for General Optimization Problems
di: Li, Jiawen, et al.
Pubblicazione: (2024)

Dual Conic Proxies for AC Optimal Power Flow
di: Qiu, Guancheng, et al.
Pubblicazione: (2023)

OR-R1: Automating Modeling and Solving of Operations Research Optimization Problem via Test-Time Reinforcement Learning
di: Ding, Zezhen, et al.
Pubblicazione: (2025)

Sobolev Training of End-to-End Optimization Proxies
di: Rosemberg, Andrew W., et al.
Pubblicazione: (2025)

Quantum-Inspired Multi Agent Reinforcement Learning for Exploration Exploitation Optimization in UAV-Assisted 6G Network Deployment
di: Taghavi, Mazyar, et al.
Pubblicazione: (2025)

Deep Reinforcement Learning Optimization for Uncertain Nonlinear Systems via Event-Triggered Robust Adaptive Dynamic Programming
di: Bai, Ningwei, et al.
Pubblicazione: (2025)