Bruno De Backer

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Constraint Programming typically uses the technique of depth-first branch and bound as the method of solving optimisation problems. Although this method can give the optimal solution, for large problems, the time needed to find the optimal can be prohibitive. This paper introduces a method for using iterative improvement techniques within a Constraint(More)
For many combinatorial problems, it is often useful to use specialized OR algorithms that allow to solve a subproblem or a simpliied version of the problem. Among these, Linear Programming algorithms, and most importantly the Simplex, are quite eecient and widely used. Many applications using Constraint Programming can take beneet from using such(More)
Constraint programming is an appealing technology to use for vehicle routing problems. Traditional linear programming models do not have the exibility or generality required by businesses wishing to model complex side constraints. This paper describes how a constraint programming framework for vehicle routing problems was implemented using ILOG Solver. A(More)
We present an estimation and forecasting method, based on a differential evolution MCMC method, for inference in GARCH models subjected to an unknown number of structural breaks at unknown dates. We treat break dates as parameters and determine the number of breaks by computing the marginal likelihoods of competing models. We allow for both recurrent and(More)
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