Supercharging Plant Configurations using Z3
Why You Should Constrain Your Machine Learned Models
Contextual Optimization: Bridging Machine Learning and Operations
A Computational Study of Constraint Programming Approaches for Resource-Constrained Project Scheduling with Autonomous Learning Effects
Strengthening of feasibility cuts in logic-based Benders decomposition
Learning Variable Activity Initialisation for Lazy Clause Generation Solvers
A*-based Compilation of Relaxed Decision Diagrams for the Longest Common Subsequence Problem
Partitioning Students into Cohorts during COVID-19
A Two-Phases Exact Algorithm for Optimization of Neural Network Ensemble
Complete Symmetry Breaking Constraints for the Class of Uniquely Hamiltonian Graphs
Heavy-Tails and Randomized Restarting Beam Search in Goal-Oriented Neural Sequence Decoding
Combining Constraint Programming and Temporal Decomposition Approaches
Scheduling of an Industrial Formulation Plant
The Traveling Social Golfer Problem: the case of the Volleyball Nations League
Towards a Compact SAT-based Encoding of Itemset Mining Tasks
A Pipe Routing Hybrid Approach based on A-Star Search and Linear Programming
MDDs boost equation solving on discrete dynamical systems
Variable Ordering for Decision Diagrams: A Portfolio Approach
Two Deadline Reduction Algorithms for Scheduling Dependent Tasks on Parallel Processors
Improving the Filtering of Branch-And-Bound MDD solver
On the Usefulness of Linear Modular Arithmetic in Constraint Programming
Injecting Domain Knowledge in Neural Networks: a Controlled Experiment on a Constrained Problem
Learning Surrogate Functions for the Short-Horizon Planning in Same-Day Delivery Problems
Between Steps: Intermediate Relaxations between big-M and Convex Hull Formulations
Logic-Based Benders Decomposition for an Inter-modal Transportation Problem
Checking Constraint Satisfaction
Finding Subgraphs with Side Constraints
Short-term scheduling of production fleets in underground mines using CP-based LNS
Learning to Reduce State-Expanded Networks for Multi-Activity Shift Scheduling
SeaPearl: A Constraint Programming Solver guided by Reinforcement Learning
Learning to Sparsify Travelling Salesman Problem Instances
Optimized Item Selection to Boost Exploration for Recommender Systems
Improving Branch-and-Bound using Decision Diagrams and Reinforcement Learning
Physician Scheduling During a Pandemic.