Search

International audience; HOME I/O is a home simulation for STEM (Science, Technology, Engineering and Mathematics) education. This software is the result of an R&D project between the CReSTIC laboratory of the University of Reims Champagne-Ardenne (URCA) and Real Games, partially funded by the French Ministry of Education. The main idea, from the beginning of the project, was to bring a virtual house into the classroom, adapted to learners and teachers and usable from college to university. HOME I/O is provided with CONNECT I/O, a software controller that can also be used as a gateway to connect to external equipment (PLC, microcontroller, Matlab, Labview...) using the Modbus TCP, OPC DA, OPC UA protocols... Feedback from teachers and students has been taken into account by regularly updating HOME I/O with new modules and new features such as the integration of Scratch 2.0 (2017) and the integration of Python 3.x (2019). HOME I/O is used in several French universities to introduce students to continuous control (with Labview for example), sequential control, SCADA (often with CONNECT I/O) as well as for IoT training (MQTT, Node-RED...). HOME I/O is used during lectures, tutorials, practical work or projects, allowing new teaching strategies to be developed. FACTORY I/O (https://factoryio.com/) is a new generation of 3D simulation software for industrial systemsFACTORY I/O is a new generation of 3D industrial system simulation software for training in programmable logic controllers (PLCs) and automation technologies. FACTORY I/O is intended for technical and professional education (high schools, IUT, BTS, engineering schools, licenses, masters...). It uses the same technologies as HOME I/O and is the successor of the ITS PLC software [1]. In this paper we will present these two tools as well as the analysis of the feedback of 77 students from three university courses: Licence 3 EEA (Electronics, Electrotechnics and Automation), first year of the A2I (Automatic and Industrial Computing Engineer) engineering cycle and university preparatory classes (CUPGE). This analysis allows us to understand the perception of the software (usefulness, playfulness, ...) and the skills that students say they have worked on (on the model of the evaluation of training by learners); HOME I/O est une simulation de maison pour l'enseignement des STEM (Sciences, Technologies, Ingénierie et Mathématiques). Ce logiciel est le résultat d'un projet de R&D entre le laboratoire CReSTIC de l'Université de Reims Champagne-Ardenne (URCA) et Real Games, partiellement financé par le ministère de l’Éducation Nationale. L'idée principale, dès le début du projet, a été d'amener une maison virtuelle dans la salle de cours, adaptée aux apprenants et aux enseignants et utilisable du collège à l'université. HOME I/O est fourni avec CONNECT I/O, automate logiciel pouvant également servir de passerelle pour se connecter à des équipements externes (API, microcontrôleur, Matlab, Labview…) au moyen des protocoles Modbus TCP, OPC DA, OPC UA... Les retours des enseignants et des étudiants ont été pris en compte en mettant régulièrement à jour HOME I/O avec de nouveaux modules et de nouvelles fonctionnalités comme l'intégration de Scratch 2.0 (2017) et l'intégration de Python 3.x (2019). HOME I/O est utilisé dans plusieurs universités françaises pour initier les étudiants à la commande continue (avec Labview par exemple), à la commande séquentielle, au SCADA (souvent avec CONNECT I/O) ainsi que pour la formation à l’IoT (MQTT, Node-RED…). HOME I/O est utilisé pendant les cours magistraux, les travaux dirigés, les travaux pratiques ou les projets, permettant ainsi d'élaborer de nouvelles stratégies d'enseignement. FACTORY I/O (https://factoryio.com/) est une nouvelle génération de logiciel de simulation 3D de systèmesIndustriels pour la formation aux automates programmables industriels (API) et aux technologies de l’automatisation. FACTORY I/O est destiné à l’enseignement technique et professionnel (lycées, IUT, BTS, écoles d’ingénieurs, licences, master…). Il utilise les mêmes technologies que HOME I/O et, est le successeur du logiciel ITS PLC [1]. Dans cette communication nous présenterons ces deux outils ainsi que l’analyse des retours d’expérience de 77 étudiants de trois filières universitaires : Licence 3 EEA (Electronique, Electrotechnique et Automatique), première année de cycle d’ingénieur A2I (Ingénieur Automatique et Informatique Industrielle) et de classe préparatoires universitaires (CUPGE). Cette analyse nous permet de comprendre la perception des logiciels (utilité, aspect ludiques, …) et les compétences que les étudiants disent avoir travaillé (sur le modèle de l’évaluation des formations par les apprenants)

The main purpose of this article is to present the use of R programming language in cartographic visualization demonstrating using machine learning methods in geographic education. Current trends in education technologies are largely influenced by the possibilities of distance-learning, e-learning and self- learning. In view of this, the main tendencies in modern geographic education include active use of open source GIS and publicly available free geospatial datasets that can be used by students for cartographic exercises, data visualization and mapping, both at intermediate and advanced levels. This paper contributes to the development of these methods and is fully based on the datasets and tools available for every student: the R programming language and the free open source datasets. The case study demonstrated in this paper show the examples of both physical geographic mapping (geomorphology) and socio-economic geography (regional mapping) which can be used in the classes and in self-learning. The objective of this research includes geomorphological modelling of the terrain relief in Italy and regional mapping. The data include DEM SRTM90 and datasets on regional borders of Italy embedded in R packages ‘maps’ and ‘mapdata’. Modelling references to the characteristics of slope, aspect, hillshade and elevation, their visualization using R packages: ‘raster’ and ‘tmap’. Regional mapping of Italy was made using main package ‘ggmap’ with the ‘ggplot2’ as a wrapper. The results present five thematic maps (slope, aspect, hillshade, elevation and regions of Italy) created in R language. Traditionally used in statistical analysis, R is less known as a perfect tool in geographic education. This paper contributes to the development of methods in geographic education by presenting new technologies of the machine learning methods of mapping.

International audience; This study evaluates the geomorphometric parameters of the topography in Ethiopia using scripting cartographic methods by applying R languages (packages 'tmap' and 'raster') and Generic Mapping Tools (GMT) for 2D and 3D topographic modelling. Data were collected from the open source repositories on geospatial data with high resolution: GEBCO with 15 arc-second and ETOPO1 with 1 arc-minute resolution and embedded dataset of SRTM 90 m in 'raster' library of R. The study demonstrated application of the programming approaches in cartographic data visualization and mapping for geomorphometric analysis. This included modelling of slope steepness, aspect and hillshade visualized using DEM SRTM90 to derive geomorphometric parameters of slope, aspect and hillshade of Ethiopia and demonstrate contrasting topography and variability climate setting of Ethiopia. The topography of the country is mapped, including Great Rift Valley, Afar Depression, Ogaden Desert and the most distinctive features of the Ethiopian Highlands. A variety of topographical zones is demonstrated on the presented maps. The results include 6 new maps made using programming console-based approach which is a novel method of cartographic visualization compared to traditional GIS software. The most important fragments of the codes are presented and technical explanations are provided. The presented series of 6 new maps contributes to the cartographic data on Ethiopia and presents the methodology of scripting mapping techniques.

Current paper presents the results of the experimental analysis on permafrost uppermost soil samples with various physical properties (moisture, porosity) tested with varied external pressure and time. The aim of this work is to test properties of the soil samples intended for the construction of buildings, railways and objects of civil infrastructure by modeled external pressure, data visualization and analysis. Variations in the soil samples were studied by analysis of the equivalent soil cohesion (Ceq) in frozen soil samples. Methods include integrated application of the laboratory experiments, methods of the statistical data analysis and 3D plotting performed by the selected LaTeX packages. Laboratory experiments were performed using KrioLab equipment ‘Sharikovy Stamp PSH-1’. The 15 series of experiments have been tested. Models of the soil strength are graphically presented and statistically analyzed showing the results of the experiment.

The Cascadia Trench is stretching along the convergent plate boundaries of Pacific Plate, North America Plate and Juan De Fuca Plate. It is an important geomorphological structural feature in the north-east Pacific Ocean. The aim of the paper is to analyse the geomorphology of the Cascadia Trench west of Vancouver Island (Canada and USA) using the GMT cartographic scripting toolset. The unique geomorphological feature of the Cascadia Trench is that the thick sediment layer completely obscures the subduction zone and abyssal hills. This results in the asymmetric profile in the cross-section of the trench. Bathymetric data were extracted from the GEBCO 2019 dataset (15 arc-second grid), sediment thickness by the GlobSed dataset. Due to the dominance of high sedimentary rate and complexity of the tectonic processes and geologic settings, Cascadia Trench develops very specific asymmetric geomorphic shape comparing to the typical V-form. The results of the geomorphic modelling show that eastern side of the trench has a gentle curvature (slope: 35.12°), partially stepped, due to the tectonic movements and faults. The opposite, oceanward side is almost completely leveled. The trench is narrow with maximal depth at the selected segment -3489 m and for the whole dataset -6201 m. The most repetitive depth is in a range -2500 to -2400 m (267 samples) and -2500 to -2600 m (261 samples). The bottom is mostly flat due to the high sedimentation rates indicating the accumulative leveling processes. Marine free-air gravity anomalies along the Cascadia Subduction Zone are characterized by weakly positive values (20 mGal) increasing rapidly in the zone of the continental slope (>200 mGal), which is associated with a decrease in thickness of the Earth’s crust.

International audience; The paper discusses the geomorphology of the Sunda Trench, an oceanic trench located in the eastern Indian Ocean along the Sumatra and Java Islands of the Indonesian archipelago. It analysis difference in depths and variation in slope steepness between the two segments of the trench: southern Java transect (108.8°E 10.10°S - 113.0°E 10.75°S) and northern Sumatra transect (97.5°E 1.1°S - 101.0°E 5.5°S). The maps and geomorphological modelling were plotted using Generic Mapping Tools (GMT). The data include high-resolution grids on topography, geology, geodesy and geophysics: GEBCO, EGM2008 EGM-2008, GlobSed. The results include modelled segments, slope gradients, and cross-section profiles. The geological processes take place in the Indian Ocean at different stages of its evolution and influence the nature of the submarine geomorphology and geomorphology of the trench that differs in two segments. Java segment has a bell- shaped data distribution in contrast to the Sumatra with bimodal pattern. Java segment has the most repetitive depths at -2,500 to -5,200 m. Sumatra transect has two peaks: 1) a classic bell-shaped peak (-4,500 m to -5,500 m); 2) shelf area (0 to -1,750 m). The data at middle depths (-1,750 to -4,500 m) have less than 300 samples. The most frequent bathymetry for the Sumatra segment corresponds to the -4,750 m to -5,000 m. Comparing to the Sumatra segment, the Java segment is deeper. For depths > -6,000 m, there are only 138 samples for Sumatra while 547 samples for Java. Furthermore, Java segment has a more symmetrical geometric shape while Sumatra segment is asymmetric, one-sided. The Sumatra segment has a steepness of 57.86° on its eastern side (facing Sumatra Island) and a contrasting 14.58° on the western part. The Java segment has a steepness of 64.34° on its northern side (facing Java Island) and 24.95° on the southern part (facing the Indian Ocean). The paper contributes to the studies of the submarine geomorphology in Indonesia.; Резиме: У раду су детаљно анализиране геоморфолошке карактеристике Сундског рова, који се пружа дуж острва Суматра и Јава у оквиру индонежанског архипелага, у источном делу Индијског океана. Познато је да је геоморфологија океанских ровова настала као резултат субдукције тектонских плоча током сложене геолошке еволуције. Упркос покушајима да се детаљно проучи његова геодинамика, природа и структура рова још увек нису довољно јасни. Конкретно, геоморфолошке карактеристике рова, формиране кроз сложене интеракције геофизичких, геолошких и тектонских фактора, у фокусу су многих истраживања. Сврха овог рада је да истражи разлике у геоморфолошким карактеристикама два различита сегмента Сундског рова (јужни део дуж острва Јава и северни део дуж острва Суматра) како би се олакшало боље разумевање структуре морског дна у североисточном делу Индијског океана. Методолошки приступ овог рада заснован је на употреби GMT, односно универзалних картографских инструмената, који су примењени у циљу конструисања графичких прилога. У овом квалитативном и квантитативном истраживању израђено је осам карата и обављен је преглед бројне литературе о истраживаном подручју.Јужни, јавански сегмент рова простире се дуж линије са следећим координа- тама (почетна и крајња тачка): 108,8°Е 10,10°S - 113,0°Е 10,75°S. Северни, суматрански сегмент лоциран је дуж линије са следећим координатама (почетна и крајња тачка) 97,5°Е 1,1°S - 101,0°Е 5,5°S. Подаци укључују растерску координатну мрежу високе резолуције о топографији, геологији, геодезији и геофизици: GEBCO, EGM2008EGM-2008, GlobSed. Представљено је и визуализовано неколико тематских карата са циљем демонстрирања просторне варијације у дистрибуцији геофизичких поља на проучаваном подручју. Карте посебно илуструју геолошке процесе који су се одвијали у источном делу Индијског океана у различитим фазама његове еволуције, а које су утицале на изглед подморске геоморфологије рова. Попречни профили су дигитализовани помоћу приступа машинског учења којег нуди GMT. Упоредна анализа оба сегмента извршена je визуелизацијом података у виду хистограма. Резултати истраживања показују да је геоморфологија рова зависна од локалних геолошких, геофизичких и тектонских карактеристика. Конкретно, јавански сегмент има дистрибуцију дубина у "облику звона", за разлику од суматранског са бимодалном дистрибуцијом. У сегменту Јаве најчешће је распрострањен појас дубина између -2.500 и -5.200 m. Сегмент Суматре има два јасно видљива врха: 1) врх у облику звона (-4.500 m до -5.500 m); 2) подручје шелфа (0 до -1.750 m). У поређењу са сегментом Суматре (северни), сегмент Јаве (јужни) је дубљи. На пример, за дубине преко -6.000 m постоји само 138 узорака за сегмент22Суматре, док постоји 547 узорака за сегмент Јаве. Даље, јавански сегмент има симетричан геометријски облик, док је сегмент Суматре углавном асиметричан. Сегмент Суматре има нагиб од 57,86° на источној страни (страна окренута према острву Суматра) и 14,58° на западној страни. Сегмент Јаве има нагиб од 64,34° на северној страни (страна окренута према острву Јава) и 24,95° у јужном делу (према Индијском океану).Значај картографске визуелизације је добро познат, јер тачно представљање података помаже да се изврши корелација и укаже на разлике у дистрибуцији геолошких и географских објеката, процеса и појава. Најчешће, традиционални GIS софтвери преовлађују у картографским истраживањима. Овај рад указује на ефикасну функционалност софтвера GMT за визуализацију геофизичких и геолошких података и за проучавање геоморфолошких карактеристика. Нејасност и неразумевање геолошких и геодинамичких процеса често проистиче из недостатка картографске визуализације која покрива одређено истраживачко подручје у правилној пројекцији и палети боја. Да би се повећала ефикасност у анализи података, представљене карте конструисане су у три различите пројекције: поликонусној, меркаторовој и азимутној пројекцији Ламберта, док су попречни профили урађени са декартовим xy координатама. Значај овог рада састоји се у мултидисциплинарном приступу који комбинује савремена картографска представ- љања података и геолошку анализу индонежанског региона. Резултати ове студије показују да су коришћење картографских метода за обраду геоинформација драгоцено средство за даља геофизичка и геоморфолошка моделовања и помоћ у бољем разумевању морског дна, јединствене скривене структуре Земљине површи- не.

International audience; Present study is focused on the satellite image processing by means of SAGA GIS. The objective of the study is assessment and analysis of the core urban areas and its spatial distribution in the limits of the city and suburbs. The study area includes Yaoundé and its surroundings, Republic of Cameroon. The methodology includes Object Based Image Segmentation (OBIS) approach by SAGA GIS. The paper presents a methodologically structured workflow used in SAGA GIS for segmentation of the Sentinel-2A image. The segmentation techniques includes adjusting technical parameters, performing neighborhood approach and post-processing procedures (unsupervised classification, number of clusters). The OBIS model and SAGA GIS were used as main methods and machine learning techniques for image segmentation. Data include Sentinel-2A satellite image with high resolution (10 m). The image was analyzed by two approaches of cell neighborhood analysis: Moore and Neumann. The results showed following numerical parameters of the computed area: the perimeter of 1,060,560 km and an area estimated for the Yaoundé city 191,745,000 km 2. The Neumann approach demonstrated better results for image clustering. The results presented automatically detected and separated segments of the city areas and other land cover types (savannah, forests, mountains). The spectral reflectance of various land cover types on a satellite image enables to group pixels of the image into classes using segmentation technique which has an important impact on the conceptual methodology of the urban mapping. The results of the image segmentation show the average values of the Neumann approach more correct in urban area than Moore approach. The accuracy assessment demonstrated 74.63% for the core urban area by using the Neumann method. The applicability of SAGA GIS for automated methods of image processing using machine learning algorithm of OBIS is presented and the advantages are discussed. The study demonstrated the effectiveness of the high-resolution Sentinel-2A for socioeconomic studies, exemplified by urban mapping where remote sensing data serve as reliable sources of geoinformation. The advantages of the OBIS are discussed with detailed explanation of the SAGA GIS workflow.

The paper discusses geomorphology of the Sunda Trench, an oceanic trench located in eastern Indian Ocean along the Sumatra and Java Islands of the Indonesian archipelago. In particular, it analysis the difference in depths and variation in slope steepness between the two segments of the trench: the southern Java transect (coordinates 108.8°E 10.10°S to 113.0°E 10.75°S) and the northern Sumatra transect (97.5°E 1.1°S to 101.0°E 5.5°S). The thematic maps and geomorphological modelling were plotted using Generic Mapping Tools (GMT). The materials include high-resolution data on topography, geology and geophysics: GEBCO 15 arc-minute resolution grid, EGM2008 2.5 minute Earth Gravitation Model of 2008, GlobSed global 5‐arc‐minute total sediment thickness and vector geological datasets. In addition to the GEBCO-based bathymetric data, geological, topographic and geophysical maps, the results include enlarged transects for the Java and Sumatra segments, their slope gradients and cross-section profiles, derived from the bathymetric GEBCO dataset. The geomorphology framework of the Sunda Trench is largely controlled by the subduction of the Australian plate underneath the Sunda microplate. The geological processes take place in basin of the Indian Ocean at different stages of its evolution and influence the nature of the submarine geomorphology and geometric shape of the trench. Sunda Trench is seismically active part of the Pacific Ring of Fire. A large number of the catastrophic earthquakes are recorded around the trench. The histograms shows variation in depths along the segments of the Sumatra and Java. The Java segment has a bell-shaped data distribution in contrast to the Sumatra with bimodal pattern. The Java segment has the most repetitive depths at -2,500 to -5,200 m. The Sumatra transect has two peaks: 1) a classic bell-shaped peak at depths -4,500 m to -5,500 m; 2) shelf area with a peak from 0 to -1,750 m. The data at middle depths (-1,750 to -4,500 m) have a frequency -6,000 m, there are only 138 samples for the Sumatra while 547 samples for Java. Furthermore, Java segment has more symmetrical geometric shape while Sumatra segment is asymmetric, one-sided. The Sumatra segment has a steepness of 57.86° on its eastern side (facing Sumatra Island) and a contrasting 14.58° on the western part. The Java segment has a steepness of 64.34° on its northern side (facing Java Island) and 24.95° on the southern part (facing Indian Ocean). The paper contributes to the studies of the submarine geomorphology in Indonesia.

This article analyzes topographical and geological settings in the Japan Archipelago for comparative raster data processing using GRASS GIS. Data include bathymetric and geological grids in NetCDF format: GEBCO, EMAG2, GlobSed, marine free‐air gravity anomaly and EGM96. Data were imported to GRASS by gdalwarp utility of GDAL and projected via PROJ library. Method‐ ology includes data processing (projecting and import), mapping and spatial analysis. Visualization was done by shell scripting using a sequence of GRASS modules: ‘d.shade’ for relief mapping, ‘r.slope.aspect’; for modelling based on DEM, ‘r.contour’ for plotting isolines, ‘r.mapcalc’ for classification, ‘r.category’ for associating labels, and auxiliary modules (d.vect, d.rast, d.grid, d.legend). The results of the geophysical visualization show that marine free‐air gravitational anomalies vary in the Sea of Japan (–30 to above 40 mGal) reflecting density inhomogeneities of the tectonic structure, and correlating with the geo‐ logical structure of the seafloor. Dominating values of geoid model are 30–45 m reflecting West Pacific rise, determined by deep density inhomogeneities associated with the mantle convention. Sediment thickness varies across the sea reflecting its geological development with density of 2 km in its deepest part and thinner in central part (Yamato Rise). The aspect map and reclassified map express gradient of the steepest descent.

Controlling risks is an important issue for companies. Far from being only the prerogative of natural disasters, the disruptions of today's supply chains can sometimes be caused by minor events amplified by the flaws of increasingly complex industrial organizations, causing severe economic losses. Risk management in supply chains is a recent theme and the proposed solutions are not yet able to meet the needs of practitioners. One of the solutions to analyse risks is using simulation. But, despite its effectiveness to cover the complexity of the chain, it still presents a major weakness which is the difficulty of implementation. The aim of this thesis is to facilitate and to adapt the simulation for risk analysis of supply chains. Thus, we have developed a modeling framework for simulation which enables an easy construction of models of supply chain structure, behavior and if the associated risks. This is done through the proposition of a set of meta-models and libraries, defined on the basis of the SCOR reference model. In addition, we proposed a translation guide for the translation of the conceptual model of supply chains into a simulation model and enabling testing risk scenario. Additionaly, we developed a library of simulation modules. A case study was conducted and the results show the relevance of the proposed approach., La maîtrise des risques est un enjeu majeur pour les entreprises. Loin d’être l’apanage des seules catastrophes naturelles, les perturbations des chaînes logistiques actuelles peuvent parfois être causées par des événements mineurs amplifiés par les failles d’organisations industrielles de plus en plus complexes. Nombreux sont les exemples de ces perturbations avec des conséquences économiques graves.La gestion des risques dans les chaines logistiques est un thème récent et les méthodes et outils actuels ne répondent pas encore totalement aux préocupations des gestionnaires de ces chaînes logistiques. Une grande aide peut être apportée par la simulation des événements affectant les chaînes. Cependant malgré son efficacité pour couvrir la complexité de la chaîne, la simulation reste encore difficile à mettre en oeuvre, notamment dans les phases de création et d’exploitation des modèles.Le but de cette thèse est de faciliter l’utilisation de la simulation pour l’analyse des risques dans les chaines logistiques. Ainsi, nous avons développé un référentiel de modélisation pour la simulation qui permet d’assurer une construction facile des modèles de la structure, du comportement et des risques inhérents aux chaines logistiques. Ce référentiel est bati sur un ensemble de metamodèles et de bibliothèques adaptés à la définition de chaînes logistiques et définis sur la base du référentiel SCOR. Ajouté à cela, nous avons proposé un guide de traduction permettant le passage d’un modèle conceptuel de chaîne logistique vers un modèle de simulation permettant de tester les scénarios de risque. Une bibliothèque de modules de simulation a été proposée pour accompagner ce passage. Une étude de cas a été menée pour tester et valider partiellement l’approche proposée.

International audience; To better support multiscale modeling and simulation, we present a multiscale time representation consisting of data types, data structures, and algorithms that collectively support the recording of past events and scheduling of future events in a discrete-event simulation. Our approach addresses the drawbacks of conventional time representations: limited range in the case of 32-or 64-bit fixed-point time values; problematic rounding errors in the case of floating-point numbers; and the lack of a universally acceptable precision level in the case of brute force approaches. The proposed representation provides both extensive range and fine resolution in the timing of events, yet it stores and manipulates the majority of event times as standard 64-bit numbers. When adopted for simulation purposes, the representation allows a domain expert to choose a precision level for his/her model. This time precision is honored by the simulator even when the model is integrated with other models of vastly different time scales. Making use of C++11 programming language features and the Discrete Event System Specification (DEVS) formalism, we implemented a simulator to test the time representation and inform a discussion on its implications for collaborative multiscale modeling efforts.

International audience; The time-line in Discrete Event Simulation (DES) is a sequence of events defined in a numerable subset of R +. When it comes from an experimental measurement, the timing of these events has a limited precision. This precision is usually well-known and documented for each instruments and procedures used for collecting experimental datas. Therefore, these instruments and procedures produce measurement results expressed using values each associated with an uncertainty quantification, given by uncertainty intervals. Tools have been developed in Continuous Systems modeling for deriving the uncertainty intervals of the final results corresponding to the propagation of the uncertainty intervals being evaluated. These tools cannot be used in DES as they are defined, and no alternative tools that would apply to DES have been developed yet. In this paper, we propose simulation algorithms, based on the Discrete Event System Specification (DEVS) formalism, that can be used to simulate and obtain every possible output and state trajecto-ries of simulations that receive input values with uncertainty quantification. Then, we present a subclass of DEVS models , called Finite Forkable DEVS (FF-DEVS), that can be simulated by the proposed algorithms. This subclass ensures that the simulation is forking only a finite number of processes for each simulation step. Finally, we discuss the simulation of a traffic light model and show the trajectories obtained when it is subject to input uncertainty.

In this thesis, we investigate the issue of optimizing the aircraft operators' demand with the airspace capacity by taking into account uncertainty in air traffic management. In the first part of the work, we identify the main causes of uncertainty of the trajectory prediction (TP), the core component underlying automation in ATM systems. We study the problem of online parameter-tuning of the TP during the climbing phase with the optimization algorithm CMA-ES. The main conclusion, corroborated by other works in the literature, is that ground TP is not sufficiently accurate nowadays to support fully automated safety-critical applications. Hence, with the current data sharing limitations, any centralized optimization system in Air Traffic Control should consider the human-in-the-loop factor, as well as other uncertainties. Consequently, in the second part of the thesis, we develop models and algorithms from a network global perspective and we describe a generic uncertainty model that captures flight trajectories uncertainties and infer their impact on the occupancy count of the Air Traffic Control sectors. This usual indicator quantifies coarsely the complexity managed by air traffic controllers in terms of number of flights. In the third part of the thesis, we formulate a variant of the Air Traffic Flow and Capacity Management problem in the tactical phase for bridging the gap between the network manager and air traffic controllers. The optimization problem consists in minimizing jointly the cost of delays and the cost of congestion while meeting sequencing constraints. In order to cope with the high dimensionality of the problem, evolutionary multi-objective optimization algorithms are used with an indirect representation and some greedy schedulers to optimize flight plans. An additional uncertainty model is added on top of the network model, allowing us to study the performances and the robustness of the proposed optimization algorithm when facing noisy context. We validate our approach on real-world and artificially densified instances obtained from the Central Flow Management Unit in Europe., Cette thèse traite de la gestion du trafic aérien et plus précisément, de l'optimisation globale des plans de vol déposés par les compagnies aériennes sous contrainte du respect de la capacité de l'espace aérien. Une composante importante de ce travail concerne la gestion del'incertitude entourant les trajectoires des aéronefs. Dans la première partie du travail, nous identifions les principales causes d'incertitude au niveau de la prédiction de trajectoires. Celle-ci est la composante essentielle à l'automatisation des systèmes de gestion du trafic aérien. Nous étudions donc le problème du réglage automatique et en-ligne des paramètres de la prédiction de trajectoires au cours de la phase de montée avec l'algorithme d'optimisation CMA-ES. La principale conclusion, corroborée par d'autres travaux de la littérature, implique que la prédiction de trajectoires des centres de contrôle n'est pas suffisamment précise aujourd'hui pour supporter l'automatisation complète des tâches critiques. Ainsi, un système d'optimisation centralisé de la gestion du trafic aérien doit prendre en compte le facteur humain et l'incertitude de façon générale. Par conséquent, la seconde partie traite du développement des modèles et des algorithmes dans une perspective globale. De plus, nous décrivons un modèle stochastique qui capture les incertitudes sur les temps de passage sur des balises de survol pour chaque trajectoire. Ceci nous permet d'inférer l'incertitude engendrée sur l'occupation des secteurs de contrôle par les aéronefs à tout moment. Dans la troisième partie, nous formulons une variante du problème classique du Air Traffic Flow and Capacity Management au cours de la phase tactique. L'intérêt est de renforcer les échanges d'information entre le gestionnaire du réseau et les contrôleurs aériens. Nous définissons donc un problème d'optimisation dont l'objectif est de minimiser conjointement les coûts de retard et de congestion tout en respectant les contraintes de séquencement aucours des phases de décollage et d'attérissage. Pour combattre le nombre de dimensions élevé de ce problème, nous choisissons un algorithme évolutionnaire multi-objectif avec une représentation indirecte du problème en se basant sur des ordonnanceurs gloutons. Enfin, nous étudions les performances et la robustesse de cette approche en utilisant le modèle stochastique défini précédemment. Ce travail est validé à l'aide de problèmes réels obtenus du Central Flow Management Unit en Europe, que l'on a aussi densifiés artificiellement.

In this thesis, we investigate the issue of optimizing the aircraft operators' demand with the airspace capacity by taking into account uncertainty in air traffic management. In the first part of the work, we identify the main causes of uncertainty of the trajectory prediction (TP), the core component underlying automation in ATM systems. We study the problem of online parameter-tuning of the TP during the climbing phase with the optimization algorithm CMA-ES. The main conclusion, corroborated by other works in the literature, is that ground TP is not sufficiently accurate nowadays to support fully automated safety-critical applications. Hence, with the current data sharing limitations, any centralized optimization system in Air Traffic Control should consider the human-in-the-loop factor, as well as other uncertainties. Consequently, in the second part of the thesis, we develop models and algorithms from a network global perspective and we describe a generic uncertainty model that captures flight trajectories uncertainties and infer their impact on the occupancy count of the Air Traffic Control sectors. This usual indicator quantifies coarsely the complexity managed by air traffic controllers in terms of number of flights. In the third part of the thesis, we formulate a variant of the Air Traffic Flow and Capacity Management problem in the tactical phase for bridging the gap between the network manager and air traffic controllers. The optimization problem consists in minimizing jointly the cost of delays and the cost of congestion while meeting sequencing constraints. In order to cope with the high dimensionality of the problem, evolutionary multi-objective optimization algorithms are used with an indirect representation and some greedy schedulers to optimize flight plans. An additional uncertainty model is added on top of the network model, allowing us to study the performances and the robustness of the proposed optimization algorithm when facing noisy context. We validate our approach on real-world and artificially densified instances obtained from the Central Flow Management Unit in Europe.; Cette thèse traite de la gestion du trafic aérien et plus précisément, de l'optimisation globale des plans de vol déposés par les compagnies aériennes sous contrainte du respect de la capacité de l'espace aérien. Une composante importante de ce travail concerne la gestion del'incertitude entourant les trajectoires des aéronefs. Dans la première partie du travail, nous identifions les principales causes d'incertitude au niveau de la prédiction de trajectoires. Celle-ci est la composante essentielle à l'automatisation des systèmes de gestion du trafic aérien. Nous étudions donc le problème du réglage automatique et en-ligne des paramètres de la prédiction de trajectoires au cours de la phase de montée avec l'algorithme d'optimisation CMA-ES. La principale conclusion, corroborée par d'autres travaux de la littérature, implique que la prédiction de trajectoires des centres de contrôle n'est pas suffisamment précise aujourd'hui pour supporter l'automatisation complète des tâches critiques. Ainsi, un système d'optimisation centralisé de la gestion du trafic aérien doit prendre en compte le facteur humain et l'incertitude de façon générale. Par conséquent, la seconde partie traite du développement des modèles et des algorithmes dans une perspective globale. De plus, nous décrivons un modèle stochastique qui capture les incertitudes sur les temps de passage sur des balises de survol pour chaque trajectoire. Ceci nous permet d'inférer l'incertitude engendrée sur l'occupation des secteurs de contrôle par les aéronefs à tout moment. Dans la troisième partie, nous formulons une variante du problème classique du Air Traffic Flow and Capacity Management au cours de la phase tactique. L'intérêt est de renforcer les échanges d'information entre le gestionnaire du réseau et les contrôleurs aériens. Nous définissons donc un problème d'optimisation dont l'objectif est de minimiser conjointement les coûts de retard et de congestion tout en respectant les contraintes de séquencement aucours des phases de décollage et d'attérissage. Pour combattre le nombre de dimensions élevé de ce problème, nous choisissons un algorithme évolutionnaire multi-objectif avec une représentation indirecte du problème en se basant sur des ordonnanceurs gloutons. Enfin, nous étudions les performances et la robustesse de cette approche en utilisant le modèle stochastique défini précédemment. Ce travail est validé à l'aide de problèmes réels obtenus du Central Flow Management Unit en Europe, que l'on a aussi densifiés artificiellement.

International audience; In this paper we present an efficient decision-making framework allowing optimization via simulation combining metaheuristics algorithms and DEVS formalism. A proposed object-oriented approach provides an universal interface between any existing DEVS models and some existing metaheuristics. To do this we explode the optimization algorithms into several actions involved in an optimization loop. Concerning the evaluation step which one can find in each metaheuristic we propose to externalize it into decision models using DEVS messages. This interconnection of components generates the following new concepts: (i) event-driven metaheuristic parametrization that allows an automatic execution of the associated algorithm; (ii) creation of dynamic and hydrid metaheuristics used for hard-optimization problems; (iii) decision support variables temporization that allows optimization on a specific time interval. We validated the effectiveness of the previous concepts through the implementation of the popular genetic algorithms and the more recent harmonic search algorithm. Furthermore the validation is completed on a real case example concerning medical treatment through a simple glycemic DEVS model. Simulation results show that the resulting treatement reduces the risk of over-tratement or under-treatement. 1. INTRODUCTION Modeling and simulation of complex systems are widely used in research and industry in order to study the behavior of systems. These studies include planning, prediction, prevision, computer-aided design, etc. tasks. To improve the performance of a studied system the modeling and simulation phases are integrated with an optimization technique. The simulation allows improving the purposes of a given model. The integration of optimization techniques into modeling and simulation relies on the evolution of the model using decisions based on previous simulation results. Usually a specialist of the domain performs the evolution manually. Therefore, it seems to be natural to try to find the set of parameters that optimizes the system performance.

The asymptotic robustness of estimators as a function of a rarity parameter, in the context of rare-event simulation, is often qualified by properties such as bounded relative error (BRE) and logarithmic efficiency (LE), also called asymptotic optimality. However, these properties do not suffice to ensure that moments of order higher than one are well estimated. For example, they do not guarantee that the variance of the empirical variance remains under control as a function of the rarity parameter. We study generalizations of the BRE and LE properties that take care of this limitation. They are named bounded relative moment of order k (BRM-k) and logarithmic efficiency of order k (LE-k), where k>=1 is an arbitrary real number. We also introduce and examine a stronger notion called vanishing relative centered moment of order k, and exhibit examples where it holds. These properties are of interest for various estimators, including the empirical mean and the empirical variance. We develop (sufficient) Lyapunov-type conditions for these properties in a setting where state-dependent importance sampling (IS) is used to estimate first-passage time probabilities. We show how these conditions can guide us in the design of good IS schemes, that enjoy convenient asymptotic robustness properties, in the context of random walks with light-tailed and heavy-tailed increments. As another illustration, we study the hierarchy between these robustness properties (and a few others) for a model of highly-reliable Markovian system (HRMS) where the goal is to estimate the failure probability of the system. In this setting, for a widely-used class of IS schemes, we show that BRM-k and LE-k are equivalent and that these properties become strictly stronger when k increases. We also obtain a necessary and sufficient condition for BRM-k in terms of quantities that can be readily verified from the parameters of the model.

International audience; -Classifier systems are rule-based control systems for the learning of more or less complex tasks. They evolve in an autonomous way through solution without any ex-ternal help. The knowledge base (the population) con-sists of rule sets (the individuals) randomly generated. The population evolves due to the use of a genetic algorithm. Solving complex problems with classifier systems involves problems to be split into simple ones. These simple prob-lems need to evolve through the main complex problem, 'co-evolving' as agents in a multi-agent system. Two different conceptual approaches are used here. First is Elitism that is inspired by Darwin, distinct agents evolving always keeping alive their best members. Second is Dis-tributed Elitism which is a logical enhancement of Elitism where agents knowledge is distributed to make the whole evolve through solution. The two concepts have shown in-teresting experimental results but are still very different in use. Mixing them seems to be a fairly good solution.