Titlebook: Integration of Constraint Programming, Artificial Intelligence, and Operations Research; 17th International C Emmanuel Hebrard,Nysret Musli

HACK

An Exact CP Approach for the Cardinality-Constrained Euclidean Minimum Sum-of-Squares Clustering Proe problem to improve several aspects of previous constraint programming approaches: lower bounds, domain filtering, and branching. Computational experiments on benchmark instances taken from the literature confirm that our approach improves our solving capability over previously-proposed exact methods for this problem.

嬰兒

Merited

邊緣帶來墨水

The HyperTrac Project: Recent Progress and Future Research Directions on Hypergraph Decompositionsd in the literature to identify tractable fragments of CSPs. However, also the computation of a concrete hypergraph decomposition is a challenging task in itself. In this paper, we report on recent progress in the study of hypergraph decompositions and we outline several directions for future research.

nitric-oxide

Local Search and Constraint Programming for a Real-World Examination Timetabling Problemboth a metaheuristic approach based on Simulated Annealing and a Constraint Programming model in MiniZinc. We compare the results of the metaheuristic approach (properly tuned) with the available MiniZinc back-ends on a large set of diverse real-world instances.

Metastasis

因無茶而冷淡

A Learning-Based Algorithm to Quickly Compute Good Primal Solutions for Stochastic Integer Programsear constraints in both stages and consistently provide near-optimal solutions. Our computing times are very competitive with those of general-purpose integer programming solvers to achieve a similar solution quality.

fiction

Reinforcement Learning for Variable Selection in a Branch and Bound AlgorithmTo our knowledge, it is the first time Reinforcement Learning has been used to fully optimise the branching strategy. Computational experiments show that our method is appropriate and able to generalise well to new instances.

ETHER

Notify

Restarting Algorithms: Sometimes There Is Free Lunchcorporated in the base algorithm or argument. We will review restarts in various settings from continuous optimization, discrete optimization, and submodular function maximization where they have delivered impressive results.