Xavier Meyer

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The Branch-and-Bound (B&B) method is a well-known optimization algorithm for solving integer linear programming (ILP) models in the field of operations research. It is part of software often employed by businesses for finding solutions to problems such as airline scheduling problems. It operates according to a divide-and-conquer principle by building a(More)
Available methods to simulate nucleotide or amino acid data typically use Markov models to simulate each position independently. These approaches are not appropriate to assess the performance of combinatorial and probabilistic methods that look for coevolving positions in nucleotide or amino acid sequences. We have developed a web-based platform that gives(More)
When crossing the road, pedestrians have to make a trade-off between saving time and avoiding any risk of injuries. Here, we studied how culture influences an individual's perception of risks when crossing a street, using survival analysis. This study is the first to use this analysis to assess cognitive mechanisms and optimality of decisions underlying(More)
Motivation Bayesian inference is widely used nowadays and relies largely on Markov chain Monte Carlo (MCMC) methods. Evolutionary biology has greatly benefited from the developments of MCMC methods, but the design of more complex and realistic models and the ever growing availability of novel data is pushing the limits of the current use of these methods.(More)
Animal movement exhibits self-similarity across a range of both spatial and temporal scales reminiscent of statistical fractals. Stressors are known to induce changes in these statistical patterns of behavior, although the direction and interpretation of such changes are not always clear. We examined whether the imposition of known hydrodynamic disruptors,(More)
An increasing number of scientific domains are confronted with the arduous task of managing large scale applications. For such applications, gradient estimations come at a large computational cost. Despite notable advances in automatic differentiation during the last years, its use in this context may reveal too costly in memory, inadequate for parallel(More)
In this article we will give firstly a classification scheme of scheduling problems and their solving methods. The main aspects under examination are the following: machine and secondary resources, constraints, objective functions, uncertainty, mathematical models and adapted solution methods. In a second part, based on this scheme, we will examine a corpus(More)
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