Marie-José Huguet

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The Flexible Job Shop scheduling Problem (FJSP) is a generalization of the classical Job Shop Problem in which each operation must be processed on a given machine chosen among a finite subset of candidate machines. The aim is to find an allocation for each operation and to define the sequence of operations on each machine so that the resulting schedule has(More)
In this paper we propose new insights based on an insertion heuristic and generalized resource constraint propagation for solving the job shop scheduling problem with minimum and maximum time-lags. To show the contribution of our propositions we propose a branch-and-bound algorithm and provide an experimental study. The results obtained conclude that our(More)
In this paper, we introduce a Yet ImprovEd Limited Discrepancy Search (YIELDS), a complete algorithm for solving Constraint Satisfaction Problems. As indicated in its name, YIELDS is an improved version of Limited Discrepancy Search (LDS). It integrates constraint propagation and variable order learning. The learning scheme, which is the main contribution(More)
This paper investigates how to adapt some discrepancy-based search methods to solve Hybrid Flow Shop (HFS) problems in which each stage consists of several identical machines operating in parallel. The objective is to determine a schedule that minimizes the makespan. We present here an adaptation of the Depth-bounded Discrepancy Search (DDS) method to(More)
Network virtualization is seen as a key networking paradigm for building diverse network services and architectures over a shared network infrastructure. Assigning network resources to virtual links and, more generally to virtual network topologies, efficiently and on-demand is one of the most challenging components of any network virtualization solution.(More)
In this paper we present a method for modeling and managing various constraints encountered in task scheduling problems. Our approach aims at characterizing feasible schedules through the analysis of the set of constraints and their interaction, regardless to any optimization criteria. This analysis is achieved by a constraint propagation process on a(More)
We consider the 2-Way Multi Modal Shortest Path Problem (2WMMSPP). Its goal is to find two multi modal paths with total minimal cost, an outgoing path and a return path. The main difficulty lies in the fact that if a private car or bicycle is used during the outgoing path, it has to be picked up during the return path. The shortest return path is typically(More)
Earth observation satellites are space sensors which acquire data, compress and record it on board, and then download it to the ground. Because of the use of more and more sophisticated compression algorithms, the amount of data resulting from an acquisition is more and more unpredictable. In such conditions, planning satellite data download activities(More)
The ATMOSTSEQCARD constraint is the conjunction of a cardinality constraint on a sequence of n variables and of n− q + 1 constraints ATMOST u on each subsequence of size q. This constraint is useful in car-sequencing and crew-rostering problems. In [18], two algorithms designed for the AMONGSEQ constraint were adapted to this constraint with a O(2n) and(More)