E-grāmata: Integration of Constraint Programming, Artificial Intelligence, and Operations Research: 18th International Conference, CPAIOR 2021, Vienna, Austria, July 5-8, 2021, Proceedings

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
ConstraintSatisfaction.- 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.