Metaheuristic Moth Flame Optimization Based Energy Efficient Clustering Protocol for 6G Enabled Unmanned Aerial Vehicle Networks

International audienceRecently, 6G networks have gained significant attention among research communities due to their development in several real-time application areas. Unmanned aerial vehicles (UAVs) became popular because of the development of 6G networks. Besides, artificial intelligence (AI) techniques can be used for effective decision-making purposes in the 6G enabled UAV environment. This study introduces a metaheuristic moth flame optimization algorithm for energy efficient clustering (MMFO-EEC) technique for 6G enabled UAV networks. The major intention of the MMFO-EEC technique is the proficient election of cluster heads (CHs) and cluster organization in 6G enabled UAV networks. The presented MMFO-EEC technique mainly employs the MFO algorithm to effectually pick out the appropriate UAVs as CHs in the network. Besides, the MMFO-EEC technique derives a fitness function comprising distinct input parameters for accomplishing improved network performance. A wide range of simulations were carried out to highlight the enhancements of the MMFO-EEC technique, and the experimental values reported improved performance of the MMFO-EEC technique over the recent approaches

Combinatorial optimization approaches for multi-part cyclic hoist scheduling problem

International audienceThis is a summary of the author’s PhD thesis, supervised by Marie-Ange Manier, Abdellah El Moudni and Mohamed Benrejeb and defended on 12 July 2011 at the “Université de Technologie de Belfort-Montbéliard”. The thesis is written in French and is available on web (http://www.theses.fr/16144587X). This work deals with the cyclic schedule of hoist activities in automated electroplating lines with a very specificvariant, called the heterogeneous multi-part jobs, where, during a cycle, different part jobs have to be treated simultaneously. The objective function of the considered problem, commonly labeled: Cyclic Hoist Scheduling Problem (CHSP), consists on the minimization of the cycle time duration

Ordonnancement cyclique multi-produits des lignes de traitement de surface : Méthodes exactes et approchées

In this thesis, we study the Cyclic Hoist Scheduling Problem (CHSP) in automated electroplating lines, when a mass production must be achieved. The CHSP is characterized by specific constraints related to processing and transport resources. To solve it in a multi-parts context, we first elaborate a 2-degree cyclic model and an associated branch and bound algorithm. Then we extend it to more complex configurations. Then, we develop a dedicated heuristic to find a feasible repetitive sequence of hoist moves that minimizes the cycle time, without a priori fixing the cycle degree. Comparisons with existing algorithms are presented to show the efficiency of the proposed heuristic. To reduce the cycle time, we integrate in the general heuristic an algorithm with a set of Minimum Part Set (MPS) configurations’. This one allows us to find the best order in which jobs should be introduced into the line. Finally, we describe a genetic algorithm approach to find a schedule which can reach the optimal 2-cycle. We finally discuss the interest of those various models, based on the promising results obtained and we provide some perspectives which could be explored.Cette thèse s’intéresse au fonctionnement cyclique multi-produits des ateliers de traitement de surface, et au problème d’ordonnancement associé (HSP), caractérisé par des contraintes fortes et atypiques, dont certaines sont liées aux ressources de transport. Dans le cas de productions en grandes séries, une commande cyclique de ces systèmes est particulièrement adaptée, permettant notamment de réduire la combinatoire de résolution, et sous réserve que les ratios de produits soient connus à l’avance. Notre objectif est de trouver le meilleur ordonnancement des tâches de traitement et de transport en un temps raisonnable. Pour cela, nous proposons une première approche, basée sur un modèle linéaire et une méthode de résolution arborescente de type séparation et évaluation. Nous présentons des modélisations pour différentes extensions du problème dit de base et nous fournissons des exemples illustratifs et des résultats sur des benchmarks. Par la suite et compte tenu de l’analyse de la littérature relative aux ordonnancements cycliques mono-produit et multi-produits, nous proposons tout d’abord une heuristique dédiée au cas multi-produits étudié, et basée sur un algorithme de liste. Avec ce dernier, nous obtenons un ordonnancement cyclique dont le degré du cycle n’est pas fixé au préalable. Enfin, nous présentons une deuxième modélisation approchée sous la forme d’un algorithme génétique pour résoudre un HSP 2-cyclique. Ces différents modèles sont validés par des tests sur des benchmarks de la littérature pour lesquels nous avons obtenus des résultats prometteurs. Nous terminons par une analyse critique des avantages et inconvénients des modèles élaborés et par quelques propositions de perspectives pour ce travail

Exact and heuristic appoaches for solving multi-parts cyclic hoist schelduling problems

Cette thèse s’intéresse au fonctionnement cyclique multi-produits des ateliers de traitement de surface, et au problème d’ordonnancement associé (HSP), caractérisé par des contraintes fortes et atypiques, dont certaines sont liées aux ressources de transport. Dans le cas de productions en grandes séries, une commande cyclique de ces systèmes est particulièrement adaptée, permettant notamment de réduire la combinatoire de résolution, et sous réserve que les ratios de produits soient connus à l’avance. Notre objectif est de trouver le meilleur ordonnancement des tâches de traitement et de transport en un temps raisonnable. Pour cela, nous proposons une première approche, basée sur un modèle linéaire et une méthode de résolution arborescente de type séparation et évaluation. Nous présentons des modélisations pour différentes extensions du problème dit de base et nous fournissons des exemples illustratifs et des résultats sur des benchmarks. Par la suite et compte tenu de l’analyse de la littérature relative aux ordonnancements cycliques mono-produit et multi-produits, nous proposons tout d’abord une heuristique dédiée au cas multi-produits étudié, et basée sur un algorithme de liste. Avec ce dernier, nous obtenons un ordonnancement cyclique dont le degré du cycle n’est pas fixé au préalable. Enfin, nous présentons une deuxième modélisation approchée sous la forme d’un algorithme génétique pour résoudre un HSP 2-cyclique. Ces différents modèles sont validés par des tests sur des benchmarks de la littérature pour lesquels nous avons obtenus des résultats prometteurs. Nous terminons par une analyse critique des avantages et inconvénients des modèles élaborés et par quelques propositions de perspectives pour ce travail.In this thesis, we study the Cyclic Hoist Scheduling Problem (CHSP) in automated electroplating lines, when a mass production must be achieved. The CHSP is characterized by specific constraints related to processing and transport resources. To solve it in a multi-parts context, we first elaborate a 2-degree cyclic model and an associated branch and bound algorithm. Then we extend it to more complex configurations. Then, we develop a dedicated heuristic to find a feasible repetitive sequence of hoist moves that minimizes the cycle time, without a priori fixing the cycle degree. Comparisons with existing algorithms are presented to show the efficiency of the proposed heuristic. To reduce the cycle time, we integrate in the general heuristic an algorithm with a set of Minimum Part Set (MPS) configurations’. This one allows us to find the best order in which jobs should be introduced into the line. Finally, we describe a genetic algorithm approach to find a schedule which can reach the optimal 2-cycle. We finally discuss the interest of those various models, based on the promising results obtained and we provide some perspectives which could be explored

Performing Enhanced Rail Formal Engineering Constraints Traceability: Transition Modes

International audience—As defined in the Council directive of 1996, the European Rail Traffic Management System (ERTMS) aims to provide the basic framework to the interoperable rail signaling and train control. Besides, traffic safety depends closely on the analysis, checking and validation of the ERTMS specifications and in the human behavior. These deals are considered on the ANR Project: PERFECT, in which this work fits. Thereby, in this paper it is proposed to use a state model approach to check and validate mode transitions of the ERTMS level 2 specifications. A scenario mode transition example is used to describe the steps of the state model algorithm and to validate it

An efficient new heuristic for the hoist scheduling problem

International audienceIn this paper, we study the hoist scheduling problem. The latter is often encountered in electroplating processes where a variety of jobs have to be processed in small quantities and in a very short amount of time. Basically, the problem consists in scheduling the hoist׳s movements in order to achieve two main objectives: Higher productivity and better product quality. In order to achieve these two goals, we first formulate the problem as a Mixed Integer Linear Programming Model. Then, due to the problem complexity, we develop an efficient heuristic procedure to obtain the hoist׳s job processing sequence. Extensive numerical experiments show that the heuristic performs extremely well compared to a lower bound obtained through the mixed linear programming model and gives the optimal makespan for a large number of problem instances. Furthermore, comparison with the best available heuristic in the literature, shows that ODEST always outperforms the heuristic and achieves an improvement (i.e., reduction) of the makespan (hence the throughput of the line) of up to 43%

A New Optimization Approach for a Home Health Care Problem

International audience— This paper deals with the home health care services. The home health care services are defined as a set of medical, paramedical and social services delivered to patients in their domicile rather than in hospital. In this paper, a new Mixed Integer Linear Programming (MILP) model is proposed to make a planning for a home health care problem. The model is optimizing routes and rosters for the health care staffs, while problem specific constraints are satisfied. This model integrates an original concept related to the human behavior (e.g. patient behavior). The MILP model is solved using the commercial optimization software Ilog-Cplex of IBM. Computational results on several benchmarks, generated from a real living-lab (GIS MADONAH) in Bourges (France), proved that the proposed model can solve real large-sized problems within acceptable computational time

Modeling and optimization of cyclic hoist schedules in an electroplating line

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Interval impulsive observer for linear systems with aperiodic discrete measurements

International audienceThis paper addresses the modeling and the design of an interval state observer for a linear time-invariant plant in presence of sporadically available measurements corrupted by unknown-but-bounded errors and noise. The interval observer is modelled as an impulsive system where an impulsive correction is made whenever a measurement is available. The nonnegativity of the observation error between two successive measurements is preserved by applying the internal positivity based on the Müller's existence theorem, while at measurement times a linear programming constraint is added. A new methodology for designing the discrete-time observer gain is proposed that guarantees both nonnegativity and stability of the estimation error. The synthesis is performed by solving a set of Bilinear Matrix Inequalities (BMIs). The theoretical result is supported by numerical simulation. Index Terms Interval observers, LTI systems, sparse output measurements, hybrid system

Guaranteed Tracking Controller for Wheeled Mobile Robot Based on Flatness and Interval Observer

International audienceThis paper proposes a guaranteed tracking controller for a Wheeled Mobile Robot (WMR) based on the differential flatness theory and the interval observer. Using the flatness property, it is possible to transform the non linear WMR model into a canonical Brunovsky form, for which it is easier to create a state feedback controller. Since, in most real applications, the WMR is subjected to uncertainties such as slip, disturbance and noise, control algorithms must be modified to take into account those uncertainties. Therefore, based on the information of the upper and lower limits of the initial condition and all the uncertainties, an interval observer that generates an envelope enclosing every feasible state trajectory is developed. After that, based on the center of the obtained interval observer, a new control law is proposed to guarantee the tracking performance of the WMR despite the existence of un-measurable states and bounded uncertainties. The closed-loop stability of the system is proven analytically using the Lyapunov theorem. A lot of numerical simulation is realized in order to demonstrate the efficiency of the suggested guaranteed tracking control scheme