The Military Inventory Routing Problem with Direct Delivery

The inventory routing problem coordinates inventory management and transportation policies when implementing vendor managed inventory replenishment, the business practice were a vendor monitors the inventory of its customers and determines a strategy to replenish each customer. The United States Army uses vendor managed inventory replenishment during combat situations to manage resupply. The military variant of the stochastic inventory routing problem considers delivery failure due to hostile actions. We formulate a Markov decision process model for the military inventory routing problem, with the objective to determine an optimal unmanned tactical airlift policy for resupplying brigade combat team elements in a combat situation using cargo unmanned aerial systems for delivery. Computational results are presented for the military inventory routing problem with direct deliveries. Results indicate that unmanned aerial systems are capable of performing brigade combat team resupply, given the dynamics of the threat situation. An experimental design is employed to determine the set of factors important in a more general context

Integrating Multiple Genetic Detection Methods to Estimate Population Density of Social and Territorial Carnivores

Spatial capture–recapture models can produce unbiased estimates of population density, but sparse detection data often plague studies of social and territorial carnivores. Integrating multiple types of detection data can improve estimation of the spatial scale parameter (σ), activity center locations, and density. Noninvasive genetic sampling is effective for detecting carnivores, but social structure and territoriality could cause differential detectability among population cohorts for different detection methods. Using three observation models, we evaluated the integration of genetic detection data from noninvasive hair and scat sampling of the social and territorial coyote (Canis latrans). Although precision of estimated density was improved, particularly if sharing σ between detection methods was appropriate, posterior probabilities of σ and posterior predictive checks supported different σ for hair and scat observation models. The resulting spatial capture–recapture model described a scenario in which scat‐detected individuals lived on and around scat transects, whereas hair‐detected individuals had larger σ and mostly lived off of the detector array, leaving hair but not scat samples. A more supported interpretation is that individual heterogeneity in baseline detection rates (λ0) was inconsistent between detection methods, such that each method disproportionately detected different population cohorts. These findings can be attributed to the sociality and territoriality of canids: Residents may be more likely to strategically mark territories via defecation (scat deposition), and transients may be more likely to exhibit rubbing (hair deposition) to increase mate attraction. Although this suggests that reliance on only one detection method may underestimate population density, integrating multiple sources of genetic detection data may be problematic for social and territorial carnivores. These data are typically sparse, modeling individual heterogeneity in λ0 and/or σ with sparse data is difficult, and positive bias can be introduced in density estimates if individual heterogeneity in detection parameters that is inconsistent between detection methods is not appropriately modeled. Previous suggestions for assessing parameter consistency of σ between detection methods using Bayesian model selection algorithms could be confounded by individual heterogeneity in λ0 in noninvasive detection data. We demonstrate the usefulness of augmenting those approaches with calibrated posterior predictive checks and plots of the posterior density of activity centers for key individuals

Adaptive network protocols to support queries in dynamic networks

Recent technological advancements have led to the popularity of mobile devices, which can dynamically form wireless networks. In order to discover and obtain distributed information, queries are widely used by applications in opportunistically formed mobile networks. Given the popularity of this approach, application developers can choose from a number of implementations of query processing protocols to support the distributed execution of a query over the network. However, different inquiry strategies (i.e., the query processing protocol and associated parameters used to execute a query) have different tradeoffs between the quality of the query's result and the cost required for execution under different operating conditions. The application developer's choice of inquiry strategy is important to meet the application's needs while considering the limited resources of the mobile devices that form the network. We propose adaptive approaches to choose the most appropriate inquiry strategy in dynamic mobile environments. We introduce an architecture for adaptive queries which employs knowledge about the current state of the dynamic mobile network and the history of previous query results to learn the most appropriate inquiry strategy to balance quality and cost tradeoffs in a given setting, and use this information to dynamically adapt the continuous query's execution

Vehicle-based modelling of traffic . Theory and application to environmental impact modelling

This dissertation addresses vehicle-based approaches to traffic flow modelling. Having regard to the inherent dynamic nature of traffic, the investigations are mainly focused on the question, how this is captured by different model classes. In the first part, the dynamics of a microscopic car-following model (SKM), presented in, is studied by means of computer simulations and analytical calculations. A classification of the model's behaviour is given with respect to the stability of high-flow states and the outflow from jam. The effects of anticipatory driving on the model's dynamics is explored, yielding results valid in general for this model class. In the second part, a new approach is introduced based on queueing theory. It can be regarded as a microscopic implementation of a state-dependent queueing model, using coupled queues where the service rates additionally depend on the conditions downstream. The concept is shown to reproduce the dynamics of free flow and wide-moving jams. This is demonstrated by comparison with the SKM and real world measurements. An analytical treatment is given as well. The phenomena of boundary induced phase transitions is further addressed, giving the complete phase diagrams of both models. Finally, the application of the queueing approach within simulation-based traffic assignment is demonstrated in regard to environmental impact modelling

Hybrid and Electric Vehicles Optimal Design and Real-time Control based on Artificial Intelligence

L'abstract è presente nell'allegato / the abstract is in the attachmen

Development of an Integrated Incident and Transit Priority Management Control System

The aim of this thesis is to develop a distributed adaptive control system which can work standalone for a single intersection to handle various boundary conditions of recurrent, non-recurrent congestion, transit signal priority and downstream blockage to improve the overall network in terms of productivity and efficiency. The control system uses link detectors’ data to determine the boundary conditions of all incoming and exit links. Four processes or modules are deployed. The traffic regime state module estimates the congestion status of the link. The incident status module determines the likelihood of an incident on the link. The transit priority module estimates if the link is flagged for transit priority based on the transit vehicle location and type. Finally, the downstream blockage module scans all downstream links and determines their recurrent blockage conditions. Three different urban incident detection models (General Regression Model, Neuro-Fuzzy Model and Binary Logit Model) were developed in order to be adopted for the incident status module. Among these, the Binary Logit Model was selected and integrated with the signal control logic. The developed Binary Logit Model is relatively stable and performs effectively under various traffic conditions, as compared to other algorithms reported in the literature. The developed signal control logic has been interfaced with CORSIM micro-simulation for rigorous evaluations with different types of signal phase settings. The proposed system operates in a manner similar to a typical pre-timed signal (with split or protected phase settings) or a fully actuated signal (with splitphase arrangement, protected phase, or dual ring phase settings). The control decisions of this developed control logic produced significant enhancement to productivity (in terms of Person Trips and Vehicle Trips) compared with the existing signal control systems in medium to heavily congested traffic demand conditions for different types of networks. Also, more efficient outcomes (in terms of Average Trip Time/Person and delay in seconds/vehicle) is achieved for relatively low to heavy traffic demand conditions with this control logic (using Split Pre-timed). The newly developed signal control logic yields greater productivity than the existing signal control systems in a typical congested urban network or closely spaced intersections, where traffic demand could be similarly high on both sides at peak periods. It is promising to see how well this signal control logic performs in a network with a high number of junctions. Such performance was rarely reported in the existing literature. The best performing phase settings of the newly developed signal control were thoroughly investigated. The signal control logic has also been extended with the logic of pre-timed styled signal phase settings for the possibility of enhancing productivity in heavily congested scenarios under a closely spaced urban network. The performance of the developed pre-timed signal control signal is quite impressive. The activation of the incident status module under the signal control logic yields an acceptable performance in most of the experimental cases, yet the control logic itself works better without the incident status module with the Split Pre-timed and Dual Actuated phase settings. The Protected Pre-timed phase setting exhibits benefits by activating the incident status module in some medium congested demand

Contributions to modeling, structural analysis, and routing performance in dynamic networks

Cette thèse apporte des contributions à la modélisation, compréhension ainsi qu’à la communication efficace d’information dans les réseaux dynamiques peuplant la périphérie de l’Internet. Par réseaux dynamiques, nous signifions les réseaux pouvant être modélisés par des graphes dynamiques dans lesquels noeuds et liens évoluent temporellement. Dans la première partie de la thèse, nous proposons un nouveau modèle de mobilité - STEPS - qui permet de capturer un large spectre de comportement de mobilité humains. STEPS mets en oeuvre deux principes fondamentaux de la mobilité humaine : l’attachement préférentiel à une zone de prédilection et l’attraction vers une zone de prédilection. Nous proposons une modélisation markovienne de ce modèle de mobilité. Nous montrons que ce simple modèle paramétrique est capable de capturer les caractéristiques statistiques saillantes de la mobilité humaine comme la distribution des temps d’inter-contacts et de contacts. Dans la deuxième partie, en utilisant STEPS, nous analysons les propriétés comportementales et structurelles fondamentales des réseaux opportunistes. Nous redéfinissons dans le contexte des réseaux dynamiques la notion de structure petit monde et montrons comment une telle structure peut émerger. En particulier, nous montrons que les noeuds fortement dynamiques peuvent jouer le rôle de ponts entre les composants déconnectés, aident à réduire significativement la longueur du chemin caractéristique du réseau et contribuent à l’émergence du phénomène petit-monde dans les réseaux dynamiques. Nous proposons une façon de modéliser ce phénomène sous STEPS. À partir d’un réseau dynamique régulier dans lequel les noeuds limitent leur mobilité à leurs zones préférentielles respectives. Nous recablons ce réseau en injectant progressivement des noeuds nomades se déplaçant entre plusieurs zones. Nous montrons que le pourcentage de tels nœuds nomades est de 10%, le réseau possède une structure petit monde avec un fort taux de clusterisation et un faible longueur du chemin caractéristique. La troisième contribution de cette thèse porte sur l’étude de l’impact du désordre et de l’irrégularité des contacts sur la capacité de communication d’un réseau dynamique. Nous analysons le degré de désordre de réseaux opportunistes réels et montrons que si exploité correctement, celui-ci peut améliorer significativement les performances du routage. Nous introduisons ensuite un modèle permettant de capturer le niveau de désordre d’un réseau dynamique. Nous proposons deux algorithmes simples et efficaces qui exploitent la structure temporelle d’un réseau dynamique pour délivrer les messages avec un bon compromis entre l’usage des ressources et les performances. Les résultats de simulations et analytiques montrent que ce type d’algorithme est plus performant que les approches classiques. Nous mettons également en évidence aussi la structure de réseau pour laquelle ce type d’algorithme atteint ses performances optimum. Basé sur ce résultat théorique nous proposons un nouveau protocole de routage efficace pour les réseaux opportunistes centré sur le contenu. Dans ce protocole, les noeuds maintiennent, via leurs contacts opportunistes, une fonction d’utilité qui résume leur proximité spatio-temporelle par rapport aux autres noeuds. En conséquence, router dans un tel contexte se résume à suivre le gradient de plus grande pente conduisant vers le noeud destination. Cette propriété induit un algorithme de routage simple et efficace qui peut être utilisé aussi bien dans un contexte d’adressage IP que de réseau centré sur les contenus. Les résultats de simulation montrent que ce protocole superforme les protocoles de routage classiques déjà définis pour les réseaux opportunistes. La dernière contribution de cette thèse consiste à mettre en évidence une application potentielle des réseaux dynamiques dans le contexte du « mobile cloud computing ». En utilisant les techniques d’optimisation particulaires, nous montrons que la mobilité peut augmenter considérablement la capacité de calcul des réseaux dynamiques. De plus, nous montrons que la structure dynamique du réseau a un fort impact sur sa capacité de calcul. ABSTRACT : This thesis contributes to the modeling, understanding and efficient communication in dynamic networks populating the periphery of the Internet. By dynamic networks, we refer to networks that can be modeled by dynamic graphs in which nodes and links change temporally. In the first part of the thesis, we propose a new mobility model - STEPS - which captures a wide spectrum of human mobility behavior. STEPS implements two fundamental principles of human mobility: preferential attachment and attractor. We show that this simple parametric model is able to capture the salient statistical properties of human mobility such as the distribution of inter-contact/contact time. In the second part, using STEPS, we analyze the fundamental behavioral and structural properties of opportunistic networks. We redefine in the context of dynamic networks the concept of small world structure and show how such a structure can emerge. In particular, we show that highly dynamic nodes can play the role of bridges between disconnected components, helping to significantly reduce the length of network path and contribute to the emergence of small-world phenomenon in dynamic networks. We propose a way to model this phenomenon in STEPS. From a regular dynamic network in which nodes limit their mobility to their respective preferential areas. We rewire this network by gradually injecting highly nomadic nodes moving between different areas. We show that when the ratio of such nomadic nodes is around 10%, the network has small world structure with a high degree of clustering and a low characteristic path length. The third contribution of this thesis is the study of the impact of disorder and contact irregularity on the communication capacity of a dynamic network. We analyze the degree of disorder of real opportunistic networks and show that if used correctly, it can significantly improve routing performances. We then introduce a model to capture the degree of disorder in a dynamic network. We propose two simple and efficient algorithms that exploit the temporal structure of a dynamic network to deliver messages with a good tradeoff between resource usage and performance. The simulation and analytical results show that this type of algorithm is more efficient than conventional approaches. We also highlight also the network structure for which this type of algorithm achieves its optimum performance. Based on this theoretical result, we propose a new efficient routing protocol for content centric opportunistic networks. In this protocol, nodes maintain, through their opportunistic contacts, an utility function that summarizes their spatio-temporal proximity to other nodes. As a result, routing in this context consists in following the steepest slopes of the gradient field leading to the destination node. This property leads to a simple and effective algorithm routing that can be used both in the context of IP networks and content centric networks. The simulation results show that this protocol outperforms traditional routing protocols already defined for opportunistic networks. The last contribution of this thesis is to highlight the potential application of dynamic networks in the context of "mobile cloud computing." Using the particle optimization techniques, we show that mobility can significantly increase the processing capacity of dynamic networks. In addition, we show that the dynamic structure of the network has a strong impact on its processing capacity