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Xavier Lorca
Researcher at École des mines de Nantes
Publications - 46
Citations - 1126
Xavier Lorca is an academic researcher from École des mines de Nantes. The author has contributed to research in topics: Constraint programming & Constraint (information theory). The author has an hindex of 11, co-authored 42 publications receiving 1088 citations. Previous affiliations of Xavier Lorca include French Institute for Research in Computer Science and Automation & Centre national de la recherche scientifique.
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Improving the Asymmetric TSP by Considering Graph Structure
TL;DR: This work provides a short survey over solving asymmetric TSP with CP and suggests new implied propagators based on general graph properties that bring robustness to pathological instances and highlight the fact that graph structure can significantly improve search heuristics behavior.
Book ChapterDOI
The increasing nvalue constraint
TL;DR: An algorithm achieving generalized arc-consistency in O(ΣDi) time, where ΣDi is the sum of domain sizes is proposed, an improvement of filtering algorithms obtained by the automaton-based or the Slide-based reformulations.
Journal ArticleDOI
Propagation engine prototyping with a domain specific language
TL;DR: This paper proposes providing a solver independent language at the modeling stage to enable the design of propagation engines and validates the proposal with a reference implementation based on the Choco solver and the MiniZinc constraint modeling language.
Book ChapterDOI
Undirected forest constraints
TL;DR: A hybrid-Consistency algorithm is described that runs in ${\mathop{\cal O}}(m+n)$ time for the resource forest constraint, a sharp improvement over the bound that is known for the directed case.
Journal ArticleDOI
Constrained optimization of landscape indices in conservation planning to support ecological restoration in New Caledonia
Dimitri Justeau-Allaire,Ghislain Vieilledent,Nicolas Rinck,Philippe Vismara,Xavier Lorca,Philippe Birnbaum +5 more
TL;DR: A novel optimization approach developed to accurately represent a broad range of conservation planning questions with spatial constraints and landscape indices, based on constraint programming based on automatic reasoning is presented.