A Multi-agent Approach for Routing on Vehicular Ad-Hoc Networks

AbstractVehicular Ad-Hoc Network is a special form of mobile ad -hoc networks (MANETs) which is a vehicle to vehicle and vehicle roadside wireless communication network. VANET is a new standard that integrates Wi-Fi, Bluetooth and other mobile connectivity protocols. The essential requirement of VANET is that it should be able to communicate in any environment irrespective of traffic densities and vehicle locations. Vehicular communications are made in fluctuating environment and should work both in urban and rural areas. Considering the large number of nodes participating in these networks and their high mobility, debates still exist about the feasibility of routing protocols. Analyzes of traditional routing protocols for MANETs demonstrated that their performance is poor in VANETs. The main problem with these protocols in VANETs environments is their route instability. Consequently, many packets are dropped and the overhead due to route repairs or failure notifications increases significantly, leading to low delivery ratios and high transmission delays. This paper introduces a multi-agent system approach to solve the problems mentioned above and improve Vehicular ad-hoc network routing

A VNS-based Heuristic for Solving the Vehicle Routing Problem with Time Windows and Vehicle Preventive Maintenance Constraints

AbstractWe address a vehicle routing problem with time windows (VRPTW) that also contains vehicle with preventive maintenance constraints (VRPTW-PM) and propose a MIP mathematical formulation as well as a general variable neighborhood search metaheuristic (VNS) to solve with large instance the problematic situation. First we create a initial solution using Solomon heuristic then we minimize the number of used routes, and then the total travelled distance by all vehicles is minimized. Computational results show the efficiency of the proposed approach

Assessing the Quality of Mobile Graphical User Interfaces Using Multi-Objective Optimization

Aesthetic defects are a violation of quality attributes that are symptoms of bad interface design programming decisions. They lead to deteriorating the perceived usability of mobile user interfaces and negatively impact the Users eXperience (UX) with the mobile app. Most existing studies relied on a subjective evaluation of aesthetic defects depending on end-users feedback, which makes the manual evaluation of mobile user interfaces human-centric, time-consuming, and error-prone. Therefore, recent studies have dedicated their effort to focus on the definition of mathematical formulas that each targets a specific structural quality of the interface. As the UX is tightly dependent on the user profile, the combi-nation and calibration of quality attributes, formulas, and users characteristics, when defining a defect, is not straightforward. In this context, we propose a fully automated framework which combines literature quality attributes with the users profile to identify aesthetic defects of MUI. More precisely, we consider the mobile user interface evaluation as a multi-objective optimization problem where the goal is to maximize the number of detected violations while minimizing the detection complexity of detection rules and enhancing the interfaces overall quality in means

Optimisation par colonies de fourmis pour le problème du sac-à-dos multi-dimensionnel

National audienceWe propose an algorithm based on the Ant Colony Optimization (ACO) meta-heuristic for solving the Multidimensional Knapsack Problem (MKP), the goal of which is to find a subset of objects that maximizes a given objective function while satisfying some resource constraints. The proposed ACO algorithm is generic, and we propose three different instantiations, corresponding to three different ways of laying and exploiting pheromone trails. We experimentally compare these three different instanciations. We then experimentally compare our ACO algorithm with two state-of-the-art genetic algorithms, showing that it obtains competitive results.Dans cet article, nous proposons d'utiliser la métaheuristique d'optimisation par colonies de fourmis (Ant Colony Optimization / ACO) pour résoudre le problème du sac à dos multidimensionnel. L'objectif est de sélectionner un sous-ensemble d'objets qui maximise une fonction utilité donnée tout en respectant certaines contraintes de ressources. Nous proposons un algorithme ACO générique pour ce problème. L'idée est de construire des solutions de façon incrémentale, par ajouts successifs d'objets à une solution partielle. A chaqueitération, l'objet à ajouter est choisi selon une probabilité dépendant de traces de ``phéromone'' et d'une information heuristique locale. On étudie trois façons de déposer (et d'exploiter) les traces de phéromone : sur les objetssélectionnés, sur les couples d'objets sélectionnés consécutivement ou sur tous les couples de sommets sélectionnés. On compare le comportement de ces trois variantes sur un ensemble d'instances ``benchmarks'' et on étudie l'influence de la phéromone sur le processus de résolution. On compare enfin l'algorithme ACO proposé avec d'autres approches

Distributed genetic algorithm for disaster relief planning

The problem studied in this paper is the management of vehicle routing in case of emergency. It is decomposed into two parts. The first one deals with the emergency planning in the event of receiving a set of requests for help after a major disaster such as in the case of an earthquake, hurricane, flood, etc. The second part concerns the treatment of contingency as the arrival of a new request or the appearance of a disturbance such as breakdowns of vehicles, the malfunction of roads, availability of airports, etc. To solve this problem we proposed a multi-agents approach using a guided genetic algorithm for scheduling vehicle routing and local search for the management of contingencies. The main objectif of our approach was to maximizing the number of saved people and minimizing the costs of the rescue operation. This approach was tested with the modified Solomon benchmarks and gave good results

3e Rencontre internationale d\u27utilisateurs d\u27UNIMARC

Journée organisée par Maria Inês Cordeiro, directrice du programme UNIMARC de l\u27IFLA (IFLA UNIMARC Core Activity) hébergé par la Bibliothèque nationale du Portugal, organisée à l\u27enssib, après Lisbonne en 2006 et Florence en 2008 et rassemblant des utilisateurs d\u27UNIMARC. La journée se divise en trois temps : un retour sur le comité permanent UNIMARC et le programme de l\u27IFLA ; la circulation des notices en France ; Utilisation d\u27UNIMARC dans le monde : au Maghreb (Tunisie, Algérie, Maroc), en Russie, en Italie et au Portugal. Les notices des interventions, en anglais et en français, proposent à la fois l\u27enregistrement audio et le diaporama accompagnant la communication

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

How to apply CBR methods in Web service composition?

International audienceThe International Conference on Signal-Image Technology & Internet-based Systems. Web-Based Information Technologies & Distributed Systems Track. December 17th - 21st 2006, Hammamet, Tunisia. pp: 230-239

CBR Method for Web Service Composition

International audienceIn this paper, we present the WeSCo CBR approach anddemonstrate how CBR techniques are applied for semi-automated WS composition. Our proposal is based mainlyon two concepts: ontologies on one hand for the descriptionof the concepts and resources needed to improve the discoveryof the relevant WS ; and Case Based Reasoning (CBR) onthe other hand, for the determination of the required busi-ness process. Our contribution consists of: 1) the definition of an ab-stract level defined by a set of domain activities in orderto limit the search space of WS and 2) a method to buildan abstract process and then a composite WS through a setof similarity computation procedures according to the CBR techniques