The CP conference is the premier international event for presenting research in all aspects of computing with constraints, including, but not restricted to: theory, algorithms, environments, languages, models, systems, and applications. CP 2024 will be the 30th edition of the CP conference and will be held in the historic city of Girona on the University of Girona campus, September 2-6, 2024.

The conference welcomes submissions that advance the state of the art of fundamental constraint-based technologies, as well as those that seek connections with other domains: for example, operations research, satisfiability, computational biology, configuration and design, computer music, entertainment, sport, cybersecurity, and AI in its broader context.

Tracks

Besides the main technical track, CP 2024 especially encourages submission to three additional specialized tracks: Application track, CP and Machine Learning track and CP and Quantum Computing track. A paper may only be submitted to either the main technical track or at most one specialized track. Special track papers will undergo the same review and publication process as that of the main technical track.

Application Track

The Application track of the International Conference on Principles and Practice of Constraint Programming targets papers that showcase the practical applications of constraint programming. These include innovative uses in various fields, such as operations research, machine learning, computational sustainability, and cybersecurity. The track is particularly interested in contributions that demonstrate the effectiveness of constraint programming in solving real-world problems, highlighting advancements in technology and applications that extend beyond traditional approaches.

In Essence, if the main track focuses on the scientific contributions made “to” CP, the Application track focuses on scientific contributions made “with” CP.

CP and Machine Learning Track

This track is dedicated to papers using machine learning approaches to improve CP solvers (e.g., learning branching heuristics, leveraging past data, solving quickly sub-problems, etc.) and, on the other side, to papers using CP to improve machine learning algorithms (e.g., providing guarantees on predictions, constraining the search space of the optimization algorithm, etc.).

CP and Quantum Computing Track

As the development of quantum computers is gaining momentum, the Constraint Programming and Quantum Computing track aims at encouraging the cross-fertilization between these two fields, both in the use of quantum computing in order to solve constrained optimization problems and in the use of constraint programming to tackle problems in the design and implementation of quantum systems.

Possible topics include, but are not limited to: quantum algorithms for constraint satisfaction and optimization problems, constraint formulations in QUBO and Ising models, experiments with Quantum Annealing and Quantum Approximate Optimization Algorithm for solving constraint problems, design and development of quantum, quantum-inspired and hybrid solvers, Constraint Programming for optimizing quantum circuits.