Modélisation électromagnétique des discontinuités uni-axiales. Application à l'étude des circulateurs planaires et de la cellule GTEM.

La méthode variationnelle multimodale (MVM) est une méthode intégrale de modélisation électromagnétque très efficace pour analyser les discontinuités uni-axiales. Cette méthode est basée sur l'identification du champs électromagnétique de part et d'autre de la discontinuité associée à la définition du coulage entre modes via l'utilisation de fonctions d'essai. Ceci lui procure de très bonnes performances notamment en rapidité et précision. L'objectif de cette thèse c'est d'adapter l'utilisation de la MVM en association avec d'autres méthodes telles que la BEM ou la TRM au traitement de circuits pésentant des discontinuités uni-axiales peu conventionnelles à travers deux applications assez différentes. La première consistait en l'étude du comportement des circulateurs planaires en technologie micro-ruban à température cryogénique. La deuxièmeapplication, consistait à élaborer un modèle électromagnétique de la cellule GTEM. ABSTRACT : The multimodal variational method (MVM) is an electromagnetic modelling integral method which is very efficient in analysing uni-axial discontinuities. This method is based on the identification on the electromagnetic field on both sides of the discontinuity in association with the mode-coupling definition by using test functions. this provides it with very good performances particulary in terms of rapidity an precision. The objective of this thesis, is to adapt the use of the MVM in addition whith other methods like the BEM or the TRM to the treatment of circuits presenting a non-conventional uni-axial discontinuities through tow rather different applications. the first one onsisted of the study of the microstrip circulators behavior at cryogenic temperature. the second application , consisted in creating an electromagnetic model of GTEM cell

Fuzzy rules for joint integration of production schedule and maintenance planning

International audienceThe relationship between production and maintenance has always been considered as a conflict in management decision. Most studies dealing with this problem adopt the approach commonly called “scheduling with availability constraints” [1] [2], where a fixed number of preventive maintenance (PM) activities are planned first then the scheduling of production jobs is optimized considering the PM actions as constraints. Recently, integrated models have been proposed to deal with the two activities simultaneously [3] [4] [5]. Multi objective techniques have been developed to find trade-off solutions to the problem. However, one of the important issues which can influence the quality and efficiency of the obtained solutions is the insertion strategy of production jobs and PM activities to avoid conflicts and gain efficiency. In this paper, we study four types of priority rules to optimize both criteria of production and maintenance simultaneously in parallel machine shop. Rules based on fuzzy logic are proposed and compared to other crisp strategies. Computational results based on a multi objective genetic algorithm show that scheduling rules based on fuzzy logic are effective

Fuzzy Rules for Joint Integration of Production Schedule and Maintenance Planning

International audienceThe relationship between production and maintenance has always been considered as a conflict in management decision. Most studies dealing with this problem adopt the approach commonly called “scheduling with availability constraints” [1] [2], where a fixed number of preventive maintenance (PM) activities are planned first then the scheduling of production jobs is optimized considering the PM actions as constraints. Recently, integrated models have been proposed to deal with the two activities simultaneously [3] [4] [5]. Multi objective techniques have been developed to find trade-off solutions to the problem. However, one of the important issues which can influence the quality and efficiency of the obtained solutions is the insertion strategy of production jobs and PM activities to avoid conflicts and gain efficiency. In this paper, we study four types of priority rules to optimize both criteria of production and maintenance simultaneously in parallel machine shop. Rules based on fuzzy logic are proposed and compared to other crisp strategies. Computational results based on a multi objective genetic algorithm show that scheduling rules based on fuzzy logic are effective

Hybrid particule swarm optimization to simultaneously minize total tardiness and unavailability system in parallel machine scheduling

International audienc

Fuzzy rules for the integration of maintenance activities in the joint scheduling of production and maintenance Planning

International audienc

Efficient bi-objective ant colony approach to minimize total tardiness and system unavailability for a parallel machine scheduling problem

In recent years, decision makers give more im- portance to the maintenance function, viewing its substantial contribution to business productivity. However, most litera- ture on scheduling studies does not take into account main- tenance planning when implementing production schedules. The achievement of production plan without taking into account maintenance activities increases the probability of machine breakdowns, and inversely, considering mainte- nance actions in production planning elongates the achieve- ment dates of orders and affects deadlines. In this paper, we propose a bi-objective model to deal with production sched- uling and maintenance planning problems simultaneously. The performance criteria considered for production and maintenance are, respectively, the total tardiness and the unavailability of the production system. The start times of preventive maintenance actions and their number are not fixed in advance but considered, with the execution dates of production tasks, as decisions variables of the problem. The solution of the integrated model is based on multi-objective ant colony optimization approach. The proposed algorithm (Pareto ant colony optimization) is compared, on the basis of several metrics, with well-known multi-objective genetic algorithms, namely NSGA-II and SPEA 2, and a hybrid particle swarm optimization algorithm. Interesting results are obtained via empirical stud

A biobjective artificial immune algorithm to the the joint production scheduling and maintenance planning problem

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Bi objective artificial immune algorithms to the joint production scheduling and maintenance planning

International audienceThis paper deals with the joint consideration of production scheduling and maintenance planning in manufacturing systems. Most studies on production scheduling deals with this problem by optimizing one criterion related to production but requirements of maintenance aspect are taken as constraints of the problem. This approach is commonly called “scheduling with availability constraints” in the literature [11][12]. In that approach, a few unavailability periods of machines are known and fixed in advance then the production jobs are scheduled according to these periods. However, maintenance and production's objectives should be considered with the same level of importance. However, performance criteria of production and maintenance are generally antagonist. Hence a solution of the joint production and maintenance problem should be a trade-off between their conflicting objectives. In this paper, a new bi objective methods based on artificial immune system is proposed where production jobs and maintenance activities are flexible and not fixed in advance

Modélisation électromagnétique des discontinuités uni-axiales (application à l'étude des circulateurs planaires et de la cellule GTEM)

La méthode variationnelle multimodale (MVM) est une méthode intégrale de modélisation électromagnétque très efficace pour analyser les discontinuités uni-axiales. Cette méthode est basée sur l'identification du champs électromagnétique de part et d'autre de la discontinuité associée à la définition du coulage entre modes via l'utilisation de fonctions d'essai. Ceci lui procure de très bonnes performances notamment en rapidité et précision. L'objectif de cette thèse c'est d'adapter l'utilisation de la MVM en association avec d'autres méthodes telles que la BEM ou la TRM au traitement de circuits pésentant des discontinuités uni-axiales peu conventionnelles à travers deux applications assez différentes. La première consistait en l'étude du comportement des circulateurs planaires en technologie micro-ruban à température cryogénique. La deuxième application, consistait à élaborer un modèle électromagnétique de la cellule GTEM.The multimodal variational method (MVM) is an electromagnetic modelling integral method which is very efficient in analysing uni-axial discontinuities. This method is based on the identification on the electromagnetic field on both sides of the discontinuity in association with the mode-coupling definition by using test functions. this provides it with very good performances particulary in terms of rapidity an precision. The objective of this thesis, is to adapt the use of the MVM in addition whith other methods like the BEM or the TRM to the treatment of circuits presenting a non-conventional uni-axial discontinuities through tow rather different applications. the first one onsisted of the study of the microstrip circulators behavior at cryogenic temperature. the second application , consisted in creating an electromagnetic model of GTEM cell.TOULOUSE-ENSEEIHT (315552331) / SudocSudocFranceF

Bi-objective branch and bound algorithms to minimize total tardiness and system unavailability on single machine problem

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