Combinatorial optimization in production and logistics systems
Combinatorial properties of Fourier-Motzkin elimination.
Combined relaxation methods for variational inequality problems over products sets.
Combined trust region methods for nonlinear least squares
Combining biometric fractal pattern and particle swarm optimization-based classifier for fingerprint recognition.
Combining evolutionary algorithms and exact approaches for multi-objective knowledge discovery
An important task of knowledge discovery deals with discovering association rules. This very general model has been widely studied and efficient algorithms have been proposed. But most of the time, only frequent rules are seeked. Here we propose to consider this problem as a multi-objective combinatorial optimization problem in order to be able to also find non frequent but interesting rules. As the search space may be very large, a discussion about different approaches is proposed and a hybrid...
Combining odometry and visual loop-closure detection for consistent topo-metrical mapping
We address the problem of simultaneous localization and mapping (SLAM) by combining visual loop-closure detection with metrical information given by a robot odometry. The proposed algorithm extends a purely appearance-based loop-closure detection method based on bags of visual words [A. Angeli, D. Filliat, S. Doncieux and J.-A. Meyer, IEEE Transactions On Robotics, Special Issue on Visual SLAM 24 (2008) 1027–1037], which is able to detect when the robot has returned back to a previously visited...
Combining Odometry and Visual Loop-Closure Detection for Consistent Topo-Metrical Mapping
We address the problem of simultaneous localization and mapping (SLAM) by combining visual loop-closure detection with metrical information given by a robot odometry. The proposed algorithm extends a purely appearance-based loop-closure detection method based on bags of visual words [A. Angeli, D. Filliat, S. Doncieux and J.-A. Meyer, IEEE Transactions On Robotics, Special Issue on Visual SLAM24 (2008) 1027–1037], which is able to detect when the robot has returned back to a previously visited...
Comment construire un graphe PERT minimal
Compactly epi-Lipschitzian convex sets and functions in normed spaces.
Comparaison d'algorithmes de plus courts chemins sur des graphes routiers de grande taille
Comparaison de deux méthodes de résolution d'un problème combinatoire quadratique
Comparaison expérimentale d'algorithmes pour les problèmes de recouvrement et de maximisation d'une fonction pseudo-booléenne
Comparaisons par paires : une interprétation et une généralisation de la méthode des scores
Comparing classification tree structures : a special case of comparing -ary relations
Comparing classification tree structures : a special case of comparing -ary relations II
Comparing classification tree structures: A special case of comparing q-ary relations II
Comparing q-ary relations on a set of elementary objects is one of the most fundamental problems of classification and combinatorial data analysis. In this paper the specific comparison task that involves classification tree structures (binary or not) is considered in this context. Two mathematical representations are proposed. One is defined in terms of a weighted binary relation; the second uses a 4-ary relation. The most classical approaches to tree comparison are discussed in the context...
Comparing classification tree structures: a special case of comparing q-ary relations
Comparing q-ary relations on a set of elementary objects is one of the most fundamental problems of classification and combinatorial data analysis. In this paper the specific comparison task that involves classification tree structures (binary or not) is considered in this context. Two mathematical representations are proposed. One is defined in terms of a weighted binary relation; the second uses a 4-ary relation. The most classical approaches to tree comparison are discussed in the context...
Comparing imperfection ratio and imperfection index for graph classes
Perfect graphs constitute a well-studied graph class with a rich structure, reflected by many characterizations with respect to different concepts. Perfect graphs are, for instance, precisely those graphs where the stable set polytope coincides with the fractional stable set polytope . For all imperfect graphs it holds that . It is, therefore, natural to use the difference between the two polytopes in order to decide how far an imperfect graph is away from being perfect. We discuss three...
Comparing Imperfection Ratio and Imperfection Index for Graph Classes
Perfect graphs constitute a well-studied graph class with a rich structure, reflected by many characterizations with respect to different concepts. Perfect graphs are, for instance, precisely those graphs G where the stable set polytope STAB(G) coincides with the fractional stable set polytope QSTAB(G). For all imperfect graphs G it holds that STAB(G) ⊂ QSTAB(G). It is, therefore, natural to use the difference between the two polytopes in order to decide how far an imperfect graph is away...