Integration of Constraint Programming, Artificial Intelligence, and Operations Research

.- Backbone-based Predict and Search for Pseudo-Boolean Optimization.- CORL: A Reinforcement Learning Framework for Combinatorial Optimization.- Enhancing Scalability in Distributed Flexible Flowshop Scheduling: A Hybrid RL-CP approach.- Augmenting the Filtering of the Multidimensional Knapsack Constraint using Lagrange Multipliers Alterations.- Learning to Choose Branching Rules for Nonconvex MINLPs.- Imitation-Guided World Models for Multi-Agent Train Rescheduling.- Clustering for Relaxed and Restricted Decision Diagram Bounds: When It Works and Why.- A Scalable Learning Approach for Efficient Computation of Independent Set and Cover Variants.- Computing Minimax Regret by Bounding the Weight Space From Within and Without.- Resolution Meets Cutting Planes: Introducing Hypercube Linear Resolution.- Transit Network Design with Two-Level Demand Uncertainties: A Machine Learning and Contextual Stochastic Optimization Framework.- Improving the planning of stochastic tasks with availability windows using prediction.- Resource-Constrained Project Scheduling Problem with Transfer Times using Secondary Resources with Instant Self-transfers.- No-Opponent-Cycle Propagators for Solving Parity Games.- Contextual Preference Distribution Learning.- Multi-objective Maximum Satisfiability by Single-objective Implicit Hitting Set Optimization.- Cost-Minimal Parameter Correction Subsets for Unsatisfiable Constraint Problems.- Towards Solving Polynomial-Objective Integer Programming with Hypergraph Neural Networks.- Integrating Bayesian Optimization and Combinatorial Optimization for LEO Satellite Constellation Design.- Explainability Results for the Rotating Workforce Scheduling Problem.- Generalised Arc Consistency via the Synchronised Product of Finite Automata with respect to a Constraint.- Open-Source Implementation of Slack Induction by String Removals for Routing and Orienteering Problems.- Heuristic Multiobjective Discrete Optimization using Restricted Decision Diagrams.- Exact Synthetic Populations for Scalable Societal and Market Modeling.- Optimization over Trained (and Sparse) Neural Networks: A Surrogate within a Surrogate.- Introducing automatically derived subproblem relaxations in a logic-based Benders decomposition solver.- A hybrid learning-based matheuristic to solve the vehicle routing problem with stochastic demands.- Scheduling Data Transfers with Priorities for Space Missions.- BaB-PoNN: A Bit-Exact Branch-and-Bound Framework for Verified Robustness of Posit Neural Networks.- Probing Features for Automatic Algorithm Selection for Pseudo- Boolean Optimization.- Singleton Node Consistency for Quadratic Assignment Problems in Cost Function Networks.- Exact Certification of Data-Poisoning Attacks Using Mixed-Integer Programming.- From Historical Templates to Hints: Selecting Effective Initializations for the Rack-Loading Problem.- GPU-Acceleration for DIDP: Design and Application to TSPTW.- Optimization over Trained Neural Networks: Going Large with Gradient-Based Algorithms.- Graph Isomorphism: Mixed-Integer Convex Optimization from First-Order Methods.- Large Neighborhood Search meets Iterative Neural Constraint Heuristics.