Decision diagrams for discrete optimization: A survey of recent advances
In the last decade, decision diagrams (DDs) have been the basis for a large array of novel
approaches for modeling and solving optimization problems. Many techniques now use DDs …
approaches for modeling and solving optimization problems. Many techniques now use DDs …
Seamless multimodal transportation scheduling
Ride-hailing services have expanded the role of shared mobility in passenger transportation
systems, creating new markets and creative planning solutions for major urban centers. In …
systems, creating new markets and creative planning solutions for major urban centers. In …
[PDF][PDF] Compact-MDD: Efficiently Filtering (s) MDD Constraints with Reversible Sparse Bit-sets.
Abstract Multi-Valued Decision Diagrams (MDDs) are instrumental in modeling
combinatorial problems with Constraint Programming. In this paper, we propose a related …
combinatorial problems with Constraint Programming. In this paper, we propose a related …
HADDOCK: A Language and Architecture for Decision Diagram Compilation
Multi-valued decision diagrams (MDDs) were introduced into constraint programming over a
decade ago as a powerful alternative to domain propagation. While effective MDD …
decade ago as a powerful alternative to domain propagation. While effective MDD …
Generalized confidence constraints
In robust optimization, finding a solution that solely respects the constraints is not enough.
Usually, the uncertainty and unknown parameters of the model are represented by random …
Usually, the uncertainty and unknown parameters of the model are represented by random …
Seamless multimodal transportation scheduling
Ride-hailing services have expanded the role of shared mobility in passenger transportation
systems, creating new markets and creative planning solutions for major urban centers. In …
systems, creating new markets and creative planning solutions for major urban centers. In …
MDDs: Sampling and probability constraints
We propose to combine two successful techniques of Artificial Intelligence: sampling and
Multi-valued Decision Diagrams (MDDs). Sampling, and notably Markov sampling, is often …
Multi-valued Decision Diagrams (MDDs). Sampling, and notably Markov sampling, is often …
Efficient operations between mdds and constraints
V Jung, JC Régin - International Conference on Integration of Constraint …, 2022 - Springer
Many problems can be solved by performing operations between Multi-valued Decision
Diagrams (MDDs), for example in music or text generation. Often these operations involve …
Diagrams (MDDs), for example in music or text generation. Often these operations involve …
Decision diagrams: constraints and algorithms
G Perez - 2017 - theses.hal.science
Multivalued Decision Diagrams (MDDs) are efficient data structures widely used in several
fields like verification, optimization and dynamic programming. In this thesis, we first focus on …
fields like verification, optimization and dynamic programming. In this thesis, we first focus on …
Markov Constraint as Large Language Model Surrogate
This paper presents NgramMarkov, a variant of the Markov constraints. It is dedicated to text
generation in constraint programming (CP). It involves a set of n-grams (ie, sequence of n …
generation in constraint programming (CP). It involves a set of n-grams (ie, sequence of n …