Integration of Constraint Programming, Artificial Intelligence, and Operations Research
Description
This book constitutes the proceedings of the 21st International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2024, held in Uppsala, Sweden, during May 28-31, 2024.
The 33 full papers and the 9 short papers presented in the proceedings were carefully reviewed and selected from a total of 104 submissions.
The content of the papers focus on new techniques or applications in the area and foster the integration of techniques from different fields dealing with large and complex problems.
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Content
Online optimization of a dial-a-ride problem with the integral primal simplex.- A Constraint Programming Model for the Electric Bus Assignment Problem with Parking Constraints.- Acquiring Constraints for a Non-linear Transmission Maintenance Scheduling Problem.- Effciently Mining Closed Interval Patterns with Constraint Programming.- Local Alterations of the Lagrange Multipliers for Enhancing the Filtering of the AtMostNValue.- Single Constant Multiplication for SAT.- Towards a Generic Representation of Combinatorial.- Problems for Learning-Based Approaches.- Accelerating Continuous Variable Coherent Ising Machines via Momentum.- Decision-focused predictions via pessimistic bilevel optimization: a computational study.- Bi-Objective Discrete Graphical Model Optimization.- An Exploration of Exact Methods for Effective Network Failure Detection and Diagnosis.- UNSAT Solver Synthesis via Monte Carlo Forest Search.- A hybrid approach integrating Generalized Arc Consistency and Differential Evolution for global optimization.- Assessing Group Fairness with Social Welfare Optimization.- Modeling and Exploiting Dominance Rules for Discrete Optimization with Decision Diagrams.- ViolationLS: Constraint-Based Local Search in CP-SAT.- ULD Build-Up Scheduling with Logic-Based Benders Decomposition.- A decomposition approach for a capacitated multi-vehicle covering tour problem with intermediate facilities.- Don't Explain Noise: Robust Counterfactuals for Randomized Ensembles.- Certifying MIP-based Presolve Reductions for 0-1 Integer Linear Programs.- Learning to Solve Job Shop Scheduling under Uncertainty.
