Cover Image

Parallel Batch Scheduling With Incompatible Job Families Via Constraint Programming

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Huertas, Jorge A., Van Hentenryck, Pascal
Format:	Preprint
Published:	2024
Subjects:	Systems and Control Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

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

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

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

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

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

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

Energy-Aware Model Predictive Control for Batch Manufacturing System Scheduling Under Different Electricity Pricing Strategies
by: Li, Hongliang, et al.
Published: (2025)

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

Optimization Learning
by: Van Hentenryck, Pascal
Published: (2025)

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

Markov Decision Process and Approximate Dynamic Programming for a Patient Assignment Scheduling problem
by: O'Reilly, Malgorzata M., et al.
Published: (2024)

Multiclass Queue Scheduling Under Slowdown: An Approximate Dynamic Programming Approach
by: Dong, Jing, et al.
Published: (2025)

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

Reliably Learn to Trim Multiparametric Quadratic Programs via Constraint Removal
by: Hou, Zhinan, et al.
Published: (2024)

Sensitivity Analysis for Piecewise-Affine Approximations of Nonlinear Programs with Polytopic Constraints
by: Gharavi, Leila, et al.
Published: (2024)

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

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

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

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

Boosting Column Generation with Graph Neural Networks for Joint Rider Trip Planning and Crew Shift Scheduling
by: Lu, Jiawei, et al.
Published: (2024)

Modeling Nonlinear Control Systems via Koopman Control Family: Universal Forms and Subspace Invariance Proximity
by: Haseli, Masih, et al.
Published: (2023)

Control Forward-Backward Consistency: Quantifying the Accuracy of Koopman Control Family Models
by: Haseli, Masih, et al.
Published: (2026)

Formally Proving Invariant Systemic Properties of Control Programs Using Ghost Code and Integral Quadratic Constraints
by: Khalife, Elias, et al.
Published: (2025)

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

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

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

Machine Learning-assisted Dynamics-Constrained Day-Ahead Energy Scheduling
by: Tuo, Mingjian, et al.
Published: (2023)

Parametric Reachable Sets Via Controlled Dynamical Embeddings
by: Harapanahalli, Akash, et al.
Published: (2025)

EASE: Energy-Aware Job Scheduling for Vehicular Edge Networks With Renewable Energy Resources
by: Perin, Giovanni, et al.
Published: (2021)

Feedback Optimization with State Constraints through Control Barrier Functions
by: Delimpaltadakis, Giannis, et al.
Published: (2025)

Probabilistic Trajectory Design Via Approximate Gaussian Mixture Steering
by: Fife, William, et al.
Published: (2024)

Control Barrier Function Based Design of Gradient Flows for Constrained Nonlinear Programming
by: Allibhoy, Ahmed, et al.
Published: (2022)

Two Roads to Koopman Operator Theory for Control: Infinite Input Sequences and Operator Families
by: Haseli, Masih, et al.
Published: (2025)

Reconfigurable Earth Observation Satellite Scheduling Problem
by: Pearl, Brycen D., et al.
Published: (2025)

Worst-Case Services and State-Based Scheduling
by: Xu, Yike, et al.
Published: (2021)

Dynamic Transfer Policies for Parallel Queues
by: Chan, Timothy C. Y., et al.
Published: (2024)

Line-Search Filter Differential Dynamic Programming for Optimal Control with Nonlinear Equality Constraints
by: Xu, Ming, et al.
Published: (2025)

Performance Evaluation of Damping Systems in Civil Engineering Structures Via Minimal Sensor
by: He, Xinhao, et al.
Published: (2024)