Papers by Abdallah Elkhyari
Ce travail a et e r ealis e au sein de l' equipe Contraintes du d epartement Informatique, et de ... more Ce travail a et e r ealis e au sein de l' equipe Contraintes du d epartement Informatique, et de l' equipe Syst emes Logistiques et de Production du d epartement Automatique Productique de l' Ecole Nationale Sup erieure des Techniques Industrielles et des Mines de Nantes. Je tiens tout d'abord a remercier Monsieur Patrice Boizumault, mon directeur de th ese, Professeur a l'Universit e de Caen, pour m'avoir encadr e tout au long de cette th ese. J'ai beaucoup appr eci e la libert e qu'il m'a laiss ee dans mes recherches et la con ance qu'il m'a accord ee. Qu'il soit aussi remerci e pour sa gentillesse, sa disponibilit e et ses encouragements. Je tiens a remercier tr es sinc erement mes deux co-encadrants : Madame Christelle Gu eret, Ma^ tre de conf erences au d epartement Automatique Productique de l' Ecole des Mines de Nantes, et Monsieur Narendra Jussien, Ma^ tre de conf erences au d epartement Informatique de l' Ecole des Mines de Nantes. Le suivi de mes travaux, leurs conseils avis es, les echanges riches et de haut niveau, sont autant d'attentions qui m'ont assur e des conditions id eales pour mener a bien ces ann ees de th ese. Qu'ils trouvent ici l'expression de ma plus sinc ere gratitude. J'adresse mes sinc eres remerciements a Monsieur G erard Verfaillie, Directeur de recherches au Laboratoire d'Analyse et d'Architecture des Syst emes LAAS-CNRS de Toulouse, ainsi qu' a Monsieur Aziz Moukrim, Ma^ tre de conf erences a l'Universit e de Technologie de Compi egne, pour l'int erêt qu'ils ont port e a mon travail en acceptant d'être rapporteurs de cette th ese. J'ai particuli erement appr eci e les discussions enrichissantes avec chacun d'eux, tant du point de vue scienti que que sur le plan humain. Leurs remarques constructives sur mon travail m'ont et e et continuent de m'être tr es pro tables. Merci egalement a Monsieur Fr ed eric Benhamou, Professeur a l'Universit e de Nantes, qui m'a fait l'honneur de pr esider le jury de ma th ese. Je voudrais egalement remercier tous les membres des deux equipes Contraintes et Syst emes Logistiques et de Production, ainsi qu' a tous les doctorants du d epartement Informatique, pour leur gentillesse, leur amiti e et leur soutien. Je ne remercierai jamais assez ma femme qui m'a support e pendant toutes ces ann ees de th ese, et qui m'a beaucoup aid e et encourag e. Bien sûr, je voudrais remercier ma famille, en particulier mes parents, a qui je dois beaucoup. 1. Une ressource est dite renouvelable si elle est de nouveau disponible apr es son utilisation par une activit e.
Programmation par Contraintes étendue pour résoudre le RCPSP dynamique et quelques extensions
HAL (Le Centre pour la Communication Scientifique Directe), Feb 26, 2003
Conflict-based repair techniques for solving dynamic scheduling problems
HAL (Le Centre pour la Communication Scientifique Directe), Sep 8, 2002
Progresses in early radiological diagnosis of Parkinson′s disease
China Medical Herald, 2011
With the rapid development of medical imaging technology and the advanced understanding of Parkin... more With the rapid development of medical imaging technology and the advanced understanding of Parkinson ′s dis-ease(PD) from the view of functional imaging,the functional imaging techniques represented by single photon emission to-mography/CT(SPECT/CT),positron emission tomography/CT(PET/CT) and magnetic resonance spectroscopy(MRS),can show changes of cerebral blood flow,metabolism,neurotransmitter,transporter and receptor,having some advantages in early diagnosis of PD.
Scheduling problems considered in the literature are often static (activities are known in advanc... more Scheduling problems considered in the literature are often static (activities are known in advance and constraints are fixed). However, every real-life schedule is subject to unexpected events. In these cases, a new solution is needed in a preferably short time and as close as possible to the current solution. In this paper, we present an exact approach for solving dynamic Resource-Constrained Project Scheduling Problems or RCPSP. This approach combines explanation-based constraint programming and operational research techniques. We present our first experimental results that show impressive improvements in both computation time and stability when comparing our approach to a re-execution from scratch.
Programmation par Contraintes étendue pour résoudre le RCPSP dynamique et quelques extensions
Scheduling problems have been studied a lot over the last decade. Due to the complexity and the v... more Scheduling problems have been studied a lot over the last decade. Due to the complexity and the variety of such problems, most works consider static problems in which activities are known in advance and constraints are fixed. However, every scheduling problem is subject to unexpected events (consider for example a new activity to schedule, or a machine breakdown). In these cases, a new solution is needed in a preferably short time taking these events into account and as close as possible to the current solution. In this paper, we present an exact approach for solving dynamic scheduling problems. This approach uses explanation-based constraint programming and operational research techniques. Our tools have been designed for a general scheduling problem: the Resource-Constrained Project Scheduling Problem (RCPSP).
Solving dynamic timetabling problems as dynamic resource constrained project scheduling problems using new constraint programming tools
Outils d'aide à la décision pour des problèmes d'ordonnancement dynamiques. (Decision support techniques for dynamic scheduling problems)
Les problemes d'ordonnancement constituent une classe importante des problemes d'optimisa... more Les problemes d'ordonnancement constituent une classe importante des problemes d'optimisation combinatoire. La plupart des travaux dans ce domaine considerent des problemes statiques pour lesquels toutes les donnees (activites, ressources, contraintes) sont connues a l'avance. En realite, ce type de problemes est tres souvent soumis aux aleas (matieres premieres livrees en retard, arrivees de nouvelles commandes, pannes de machines, etc.). Aussi, l'ordonnancement se deroule rarement comme prevu. On a alors affaire a un probleme d'ordonnancement dit dynamique. Dans cette these, nous considerons un probleme d'ordonnancement tres general, appele RCPSP (Resource Constrained Project Scheduling Problem), et proposons un systeme permettant de resoudre le cas dynamique. Bien que beaucoup de travaux concernent le RCPSP statique, seules quelques methodes sont proposees pour le cas dynamique. De plus ces methodes ne sont pas satisfaisantes. La methode que nous proposons...
The Resource Constrained Project Scheduling Problem (rcpsp) is a general scheduling problem which... more The Resource Constrained Project Scheduling Problem (rcpsp) is a general scheduling problem which consists in scheduling a set of activities taking into account temporal and resource constraints (Demeulemeester and Herroelen, 2002). Preemption is not allowed. The objective considered here is the minimization of the makespan (total duration) of the project. This problem is NP-hard (Blazewicz et al., 1983). Most work about rcpsp consider static problems in which activities are known in advance and constraints are fixed. However, every schedule is subject to unexpected events (consider for example a new activity to schedule, or a resource failure – eg. machine breakdown). When such a situation arises, a new solution taking these events into account is needed generally in a short time. Furthermore, this new solution must preferably be not too far from the previous one. Several works concern dynamic scheduling problems. But generally, they deal with very specific problems like one-machin...
Ordonnancement dynamique de projet à contraintes de ressources
The Resource Constrained Project Scheduling Problem (rcpsp) is a general scheduling problem. It c... more The Resource Constrained Project Scheduling Problem (rcpsp) is a general scheduling problem. It consists of a set of activities and a set of renewable resources. Each resource is available in a given constant amount. Each activity has a duration and requires a constant amount of resource to be processed. Preemption is not allowed. Activities are related by two sets of constraints: temporal constraints modelled through precedence constraints, and resource constraints that state that for each time period and for each resource, the total demand cannot exceed the resource capacity. The objective considered here is the minimization of the makespan (total duration) of the project. This problem is NP-hard [3]. Most work about rcpsp consider static problems in which activities are known in advance and constraints are fixed. However, every schedule is subject to unexpected events (consider for example a new activity to schedule, or a resource failure – eg. machine breakdown). When such a sit...
Scheduling problems considered in the literature are often static (activities are known in advanc... more Scheduling problems considered in the literature are often static (activities are known in advance and constraints are fixed). However, every real-life schedule is subject to unexpected events. In these cases, a new solution is needed in a preferably short time and as close as possible to the current solution. In this paper, we present an exact approach for solving dynamic Resource-Constrained Project Scheduling Problems or RCPSP. This approach combines explanation-based constraint programming and operational research techniques. We present our first experimental results that show impressive improvements in both computation time and stability when comparing our approach to a re-execution from scratch.
New tools for solving dynamic timetabling problems
2B1 CONSTRAINT PROGRAMMING FOR DYNAMIC SCHEDULING PROBLEMS(Technical session 2B : Combinatorics 1)
Combining constraint programming and genetic algorithm for dynamic scheduling problems
This paper introduces a new method based on constraint programming (CP) and genetic algorithm (GA... more This paper introduces a new method based on constraint programming (CP) and genetic algorithm (GA) for solving dynamic scheduling problems. The proposed approach allows us to handle scheduling problems with large sizes (i.e. search spaces are too large). Our idea is to break up the search space into disjoined sub-spaces by the genetic algorithm. To each individual of the population is associated a sub-space. Each sub-space is represented by a sub-CSP which is easier to solve than the original scheduling problem. Our first experimentations are addressed to the Endoscopy Unit scheduling in dynamic way.
Utilisation de la programmation par contraintes pour résoudre le RCPSP dynamique et quelques extensions
Publikationsansicht. 44868480. Utilisation de la programmation par contraintes pour le problème ... more Publikationsansicht. 44868480. Utilisation de la programmation par contraintes pour le problème d'allocation de fréquences en téléphonie cellulaire / (2002). Ducharme, Alain. Abstract. "Mémoire présenté en vue de l'obtention ...
Outils d''aide `a la d'ecision pour les probl`emes d''ordonnancement dynamique
The Resource Constrained Project Scheduling Problem (rcpsp) is a general scheduling problem. It c... more The Resource Constrained Project Scheduling Problem (rcpsp) is a general scheduling problem. It consists of a set of activities and a set of renewable resources. Each resource is available in a given constant amount. Each activity has a duration and requires a constant amount of resource to be processed. Preemption is not allowed. Activities are related by two sets of constraints: temporal constraints modelled through precedence constraints, and resource constraints that state that for each time period and for each resource, the total demand cannot exceed the resource capacity. The objective considered here is the minimization of the makespan (total duration) of the project. This problem is NP-hard . Most work about rcpsp consider static problems in which activities are known in advance and constraints are fixed. However, every schedule is subject to unexpected events (consider for example a new activity to schedule, or a resource failure -eg. machine breakdown). When such a situation arises, a new solution, taking these events into account, is needed in a preferably short time. Two classical methods used to solve such problems are: recomputing a new schedule from scratch each time an event occurs (a quite time consuming technique) and constructing a partial schedule and completing it progressively as time goes by (like in on-line scheduling problems -this is not compatible with planning purposes). Recently, Artigues et al. [1] developed a polynomial algorithm based on a flow network model to update an initial static schedule when considering the insertion of an unexpected activity. Constraint Satisfaction Problems (csp) are increasingly used for solving scheduling problems. However, dynamic csp (an extension of the csp framework where the set of variables or/and constraints evolves throughout computation ) are not as spread. We introduce here such a new method applied to dynamic rcpsp. Efficiently solving dynamic problems requires incremental addition and retraction of constraints. Even though incremental constraint addition is naturally handled by modern constraint solvers, incremental retraction of constraints is often performed with recording trace/undo information . Such an information is used to determine past effects of removed constraint that need to be undone. Explanations are a generalization of that information. An explanation is a set of constraints that justifies an action of the solver (classically value removals) i.e. as long as each constraint that appears in the explanation remains active (not removed) the value removal is valid; thus, no valid solution can be build from this partial assignment . Providing explanations for temporal binary constraints is straightforward (as they are binary mathematical relations -see ). Explanations for resource management constraints are not that easy. It is necessary to study the algorithms used for propagation (resource limitations maintenance): core-times , task-interval [6, 5] and resource-histogram . We added explanation capabilities to these techniques . Moreover, we developed a branch and bound search using explanation-based techniques (as in ) and inspired from a branch and bound algorithm from [4]. Our interactive system accepts several types of modification on the scheduling problem: temporal events (adding/removing precedence/overlapping/ disjunctive relations, modifying time-windows), activity related events (adding/removing),
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Papers by Abdallah Elkhyari