CPAIOR2024: INTERNATIONAL CONFERENCE ON THE INTEGRATION OF CONSTRAINT PROGRAMMING, ARTIFICIAL INTELLIGENCE, AND OPERATIONS RESEARCH
PROGRAM

Days: Tuesday, May 28th Wednesday, May 29th Thursday, May 30th Friday, May 31st

Tuesday, May 28th

View this program: with abstractssession overviewtalk overview

19:00-20:30 Opening Reception

Reception at the University Main Building (map) (this is about 500 metres away, towards downtown, doable in a 7-minute walk)

Wednesday, May 29th

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08:45-09:00 Session 2: Opening Remarks

All talks, posters, breaks, and lunches will be at Humanities Theatre

Map: https://link.mazemap.com/avOKVjRs

09:00-10:40 Session 3: Integrating ML and OR
09:00
Towards a Generic Representation of Combinatorial Problems for Learning-Based Approaches (abstract)
09:20
Efficient Structured Perceptron for NP-hard Combinatorial Optimization Problems (abstract)
09:40
Learning Heuristics for Combinatorial Optimization Problems on K-Partite Hypergraphs (abstract)
10:00
Explainable Algorithm Selection for the Capacitated Lot Sizing Problem (abstract)
10:20
An Improved Neuro-Symbolic Architecture to Fine-Tune Generative AI Systems (abstract)
10:40-11:10Break with Refreshments
11:10-12:30 Session 4: Constraint Programming
11:10
Proof Logging for the Circuit Constraint (abstract)
11:30
Local Alterations of the Lagrange Multipliers for Enhancing the Filtering of the AtMostNValue (abstract)
11:50
A hybrid approach integrating Generalized Arc Consistency and Differential Evolution for global optimization (abstract)
12:10
Efficiently Mining Closed Interval Patterns with Constraint Programming (abstract)
12:30-12:50 Session 5: Spotlight Talks for Posters I
12:30
A data-driven method for constraint customization in optimization models (abstract)
12:35
MaxSAT-Based Bi-Objective Boolean Optimization (abstract)
12:40
Trade-offs in Multi-objective Problems: Finding Top-k Non-dominated Solutions (abstract)
12:45
The strange case of XOR-CNF formulas: SAT Obfuscation and more (abstract)
12:50-14:00Lunch + Posters I
14:00-15:00 Session 6: Keynote I
14:00
Keynote: Decomposition to tackle large-scale discrete optimisation problems (abstract)
15:00-15:50 Session 7: Fairness
15:00
Fair Minimum Representation Clustering (abstract)
15:20
Assessing Group Fairness with Social Welfare Optimization [BEST PAPER] (abstract)
15:50-16:20Break with Refreshments
16:20-17:40 Session 8: Applications I
16:20
A Constraint Programming Model for the Electric Bus Assignment Problem with Parking Constraints (abstract)
16:40
A Benders decomposition approach for a capacitated multi-vehicle covering tour problem with intermediate facilities (abstract)
17:00
Online optimization of a dial-a-ride problem with the integral primal simplex (abstract)
17:20
A Constraint Programming Approach for Aircraft Disassembly Scheduling (abstract)
Thursday, May 30th

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09:00-10:40 Session 9: SAT
09:00
Single Constant Multiplication for SAT (abstract)
09:20
Core Boosting in SAT-Based Multi-Objective Optimization (abstract)
09:40
UNSAT Solver Synthesis via Monte Carlo Forest Search (abstract)
10:00
ViolationLS: Constraint-Based Local Search in CP-SAT (abstract)
10:20
SMT-based Repair of Disjunctive Temporal Networks with Uncertainty: Strong and Weak Controllability (abstract)
10:40-11:10Break with Refreshments
11:10-12:30 Session 10: Machine Learning + Multi-objective Optimization
11:10
Don't Explain Noise: Robust Counterfactuals for Randomized Ensembles (abstract)
11:30
Accelerating Continuous Variable Coherent Ising Machines via Momentum (abstract)
11:50
Bi-Objective Discrete Graphical Model Optimization (abstract)
12:10
Strategies for Compressing the Pareto Frontier: Application to Strategic Planning of Hydropower in the Amazon Basin (abstract)
12:30-12:50 Session 11: Spotlight Talks for Posters II
12:30
Optimal counterfactual explanations for k-Nearest Neighbors using Mathematical Optimization and Constraint Programming (abstract)
12:35
Task Generalization in Decision-Focused Learning (abstract)
12:40
On Learning CP-SAT Resolution Outcomes Before Reaching Time-Limit (abstract)
12:45
A Delta Debugger for Mixed-Integer Programming Solvers (abstract)
12:50-14:00Lunch + Posters II
14:00-15:00 Session 12: Keynote II
14:00
Keynote: Decision-Focused Learning: Foundations, State of the Art, Benchmarks and Future Opportunities (abstract)
15:00-15:40 Session 13: Decision-focused Learning
15:00
CaVE: A Cone-aligned Approach for Fast Predict-then-optimize with Binary Linear Programs (abstract)
15:20
Decision-focused predictions via pessimistic bilevel optimization: a computational study (abstract)
15:40-16:10Break with Refreshments
16:10-17:30 Session 14: Applications II
16:10
Minimizing the Cost of Leveraging Influencers in Social Networks: IP and CP Approaches (abstract)
16:30
An Exploration of Exact Methods for Effective Network Failure Detection and Diagnosis (abstract)
16:50
ULD Build-Up Scheduling with Logic-Based Benders Decomposition (abstract)
17:10
Acquiring Constraints for a Non-linear Transmission Maintenance Scheduling Problem (abstract)
19:00-22:30 Banquet at Norrlands Nation

Map: https://link.mazemap.com/dUeEazIj 

It is 900 meters from the Humanities Theatre (a walk of about 12 minutes).

Welcome drinks 19:00 - 19:30

Dinner served at 19:30

The bar opens after dinner ( until 1 am )

Friday, May 31st

View this program: with abstractssession overviewtalk overview

09:00-10:30 Session 16: Decision Diagrams + MIP
09:00
Lookahead, Merge and Reduce for Compiling Relaxed Decision Diagrams for Optimization (abstract)
09:20
Modeling and Exploiting Dominance Rules for Discrete Optimization with Decision Diagrams (abstract)
09:40
LEO: Learning Efficient Orderings for Multiobjective BDDs (abstract)
10:00
Probabilistic Lookahead Strong Branching via a Stochastic Abstract Branching Model [BEST STUDENT PAPER] (abstract)
10:30-10:50Break with Refreshments
10:50-12:10 Session 17: MIP + Optimization techniques in Neural Networks
10:50
Certifying MIP-based Presolve Reductions for 0-1 Integer Linear Programs (abstract)
11:10
Optimization Over Trained Neural Networks: Taking a Relaxing Walk (abstract)
11:30
Bound Tightening using Rolling-Horizon Decomposition for Neural Network Verification (abstract)
11:50
Robustness Verification in Neural Networks (abstract)
12:10-12:25 Session 18: Spotlight Talks for Posters III
12:10
End-to-End Classical Planning using CP and Belief Propagation (abstract)
12:15
An Imitation Learning approach for Personnel Scheduling with flexibility for On-Call Shifts (abstract)
12:20
End-to-End Verification for Subgraph Solving (abstract)
12:25-13:40Lunch + Posters III
13:40-15:00 Session 19: ML4CO in Stochastic and Uncertain Settings
13:40
Learning to Solve Job Shop Scheduling under Uncertainty (abstract)
14:00
Improving Metaheuristic Efficiency for Stochastic Optimization Problems by Sequential Predictive Sampling (abstract)
14:20
Learning Deterministic Surrogates for Robust Convex QCQP (abstract)
14:40
Learning From Scenarios for Repairable Stochastic Scheduling (abstract)
15:00-16:00 Session 20: Keynote III
15:00
Keynote: Optimization and machine learning on quantum computers: yes/no/maybe? (abstract)
16:00-16:40Closing Remarks and Break with Refreshments