NOHIS-tree nouvelle méthode de recherche de plus proches voisins (application à la recherche d'images par le contenu)

Les tailles des bases d images ont connu une croissance rapide. Elles peuvent se chiffrer actuellement en millions d objets ce qui nécessite l utilisation d un système de recherche d images par le contenu. Un tel système consiste tout d abord en la description automatique des images de la base. Les propriétés visuelles de chaque image sont représentées sous forme de vecteurs multidimensionnels appelés descripteurs. Ensuite, trouver les images similaires à une image requête revient à chercher pour chaque descripteur de l image requête les descripteurs les plus proches. Dans ce travail de thèse nous proposons une nouvelle méthode d indexation de bases multidimensionnelles avec une évolution de l algorithme de recherche de plus proches voisins. L originalité de notre index multidimensionnel est la création de formes englobantes évitant le chevauchement. En effet, le chevauchement est l un des principaux inconvénients qui ralentissent la recherche de plus proches voisins. Le nouvel index créé et son algorithme de recherche spécifique permettent d accélérer la recherche de plus proches voisins tout en effectuant une recherche à l exact. La méthode que nous avons conçue a été intégrée et évaluée dans un système réel de recherche d images par le contenu. Les résultats des expérimentations effectuées montrent sa robustesse en termes de précision et de rapidité en temps de recherche.The increasing of image databases requires the use of a content-based image retrieval system (CBIR). A such system consist first to describe automatically the images, visual properties of each image are represented as multidimensional vectors called descriptors. Next, finding similar images to the query image is achieved by searching for the nearest neighbors of each descriptor of the query image. In this thesis, we propose a new method for indexing multidimensional bases with the search algorithm of nearest neighbors adapted. The originality of our multidimensional index is the disposition of the bounding forms avoiding overlapping. Indeed, the overlapping is one of the main drawbacks that slow the search of nearest neighbors search. Our index with its search algorithm speeds the nearest neighbors search while doing an exact search. Our method has been integrated and tested within a real content-based image system. The results of tests carried out show the robustness of our method in terms of accuracy and speed in search time.ORSAY-PARIS 11-BU Sciences (914712101) / SudocSudocFranceF

Genetic Algorithm Based Approach for the Multi-Hoist Design and Scheduling Problem

International audienceElectroplating facilities often face the Cyclic Hoist Scheduling Problem when a repetitive sequence of moves is searched for the hoists. This paper addresses this optimization problem extended to the design of the workshop, where we aim to minimize both the cycle time and the number of hoists used. For this goal, we propose a genetic meta-heuristic approach which introduces a novel solution encoding to enlarge the solutions’ search space. Our encoding procedure is based on hoists’ empty moves, and includes separator characters. With the latter, weobtain solutions that were not reachable by previous approaches. Each solution obtained thanks to the genetic operators is evaluated by using a Mixed Integer Linear Program. This one checks the constraints of the problem (such as capacity constraints and soaking time bounds) and computes the smallest cycle time for a given moving sequence and its associated number of hoists. Some results are presented using benchmark instances for which our approach allows to improve the best known solutions

Clustering Weekly Patterns of Human Mobility Through Mobile Phone Data

International audienceWith the rapid growth of cell phone networks during the last decades, call detail records (CDR) have been used as approximate indicators for large scale studies on human and urban mobility. Although coarse and limited, CDR are a real marker of human presence. In this paper, we use more than 800 million CDR to identify weekly patterns of human mobility through mobile phone data. Our methodology is based on the classification of individuals into six distinct presence profiles where we focus on the inherent temporal and geographical characteristics of each profile within a territory. Then, we use an event-based algorithm to cluster individuals and we identify 12 weekly patterns. We leverage these results to analyze population estimates adjustment processes and as a result, we propose new indicators to characterize the dynamics of a territory. Our model has been applied to real data coming from more than 1.6 million individuals and demonstrates its relevance. The product of our work can be used by local authorities for human mobility analysis and urban planning

Single quay crane and multiple yard trucks scheduling problem with integration of reach-stacker cranes at port of Tripoli-Lebanon

International audienceThis paper addresses the scheduling problem in port of Tripoli-Lebanon for a single quay crane with multiple yard trucks, all containers that will be unloaded from the vessel are in the same bay. The objective is to reduce the completion time of all containers from the vessel to their store location, we used a mixed integer linear programming and a dynamic programming algorithm to solve the problem. Finally, we have compared and validated our results on real instances from the port

Integrated quay crane and yard truck scheduling problem at port of Tripoli-Lebanon

International audience<div class="Abstracts u-font-serif" id="abstracts"&gt<div class="abstract author" id="ab010" lang="en"&gt<div id="as010"&gt<p id="sp010"&gtThe scheduling problem is one of the most important operation in maritime ports. In this study we solved the scheduling problem for a single quay crane and multiple yard trucks in port of Tripoli-Lebanon. In a previous study we proposed two exact methods for this problem but we faced a problem for large instances in CPU time. For this reason, in this paper we developed a <a href="https://www.sciencedirect.com/topics/mathematics/heuristic-method" title="Learn more about heuristic method from ScienceDirect's AI-generated Topic Pages" class="topic-link"&gtheuristic method</a&gt (genetic algorithm) to obtain near optimal solution with an acceptable CPU time. The main objective of this paper is to minimize the completion time of all containers from the container vessel to its storage location and to have good results compared with real results in the port of Tripoli-Lebanon.</p&gt</div&gt</div&gt</div&g

Collision-Free Based Model for the Cyclic Multi-Hoist Scheduling Problem

International audienceIn this paper, we propose a Mixed Integer Linear Programming model for solving a hoist scheduling problem with several transportation resources. This model complements initial work that neglected the risk of collisions between hoists. This new model identifies and manages the various possible collision situations, and it is intended to be integrated as a solution evaluation module in a hybrid algorithm addressing the broader and more complex joint problem of sizing transport resources and scheduling surface treatment workshops. In this global approach, an evolutionary algorithm first generates partially feasible solutions, whose total feasibility is then verified a posteriori, thanks to the proposed new model. This model is validated through tests performed on instances of the literature

Genetic algorithm to optimize unloading of large containers vessel in port of Tripoli-Lebanon

International audienceThe quay crane scheduling problem (QCSP) in the lebanese port (Tripoli) is discussed in this study. It consists in assigning each crane to a set of bays for a given vessel, while sequencing the unloading of these bays. In a previous study, we discussed two exacts methods whose main drawback is the difficulty to obtain results for large instances. That’s why, we propose a genetic algorithm which enables us to overcome this and to get quickly near optimal solutions. We have tested and validated our method on real instances from the port of Tripoli

Exact method for single vessel and multiple quay cranes to solve scheduling problem at port of Tripoli-Lebanon

International audienceThis paper discusses the Quay Crane Scheduling Problem (QCSP) at port of Tripoli - Lebanon, determines the unloading/loading sequences of bays for quay cranes assigned to a single container vessel, provides a mixed integer programming model for the quay crane scheduling problem and proposes a dynamic programming algorithm to solve the QCSP. The objective of this paper is to minimize the completion time of unloading/loading containers and therefore to reduce the docking time of the vessel in the terminal. Finally the results of this paper are compared to the port results

Solving methods for the quay crane scheduling problem at port of Tripoli-Lebanon

International audience<div style=""&gt<font face="arial, helvetica"&gt<span style="font-size: 13px;"&gtThe quay crane scheduling problem (QCSP) is a global&nbsp;</span&gt</font&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtproblem and all ports around the world seek to solve it, to get an ac</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtceptable time of unloading containers from the vessels or loading con</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gttainers to the vessels and therefore reducing the docking time in the&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtterminal. This paper proposes three solutions for the QCSP in port of&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtTripoli-Lebanon, two exact methods which are the mixed integer linear&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtprogramming and the dynamic programming algorithm, to obtain the&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtoptimal solution and one heuristic method which is the genetic algo</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtrithm, to obtain near optimal solution within an acceptable CPU time.&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtThe main objective of these methods is to minimize the unloading or&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtthe loading time of the containers and therefore reduce the waiting&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gttime of the vessels in the terminals. We tested and validated our meth</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtods for small and large random instances. Finally, we compared the&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtresults obtained with these methods for some real instances in the port&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtof Tripoli-Lebanon.</span&gt</div&g