Localisation de plateformes logistiques en milieu urbain

Depuis une dizaine d'années, la logistique urbaine suscite l'intérêt de bon nombre de chercheurs de communauté et nationalité variées. L'objet du travail présenté ici porte sur la localisation de plateformes logistiques dans des zones urbaines denses

Plates-formes en centre ville pour la Logistique Urbaine: étude sur la ville de Marseille

International audienceCette étude, conduite dans le cadre du projet PLUME, se propose d'évaluer l'intérêt de la mise en œuvre de systèmes de distribution urbaine à partir de Zones Logistiques Urbaines. Nous visons à définir d'un point de vue organisationnel et fonctionnel les atouts économiques, environnementaux et sociétaux de ces systèmes; le but étant de fournir un cadre méthodologique pour guider leur mise en place. Un premier terrain d'analyse pour notre étude sera la ville de Marseille qui possède la particularité de disposer d'une ZLU en cœur de centre-ville avec la plate-forme logistique d'ARENC (41362 m2 d'entrepôts et de bureaux). Dans cet article, nous proposons de définir plus précisément notre problématique avant de donner un bref état de l'art des problèmes classiques de la Recherche Opérationnelle se rattachant à notre étude (Facility Location Problem, Network Design Problem et Green Logistics). Nous établissons enfin une liste d'éléments que nous chercherons à prendre en compte dans un modèle général

The City Logistics Facility Location Problem

National audienceThe aim of this work is to propose a new model that we call the City Logistics Facility Location Problem (CLFLP). Our purpose when introducing the CLFLP, is to capture essential aspects of distribution in cities, while maintaining a reasonable level of genericity and simplicity in the defintion of the problem. Practically, this model was adapted to the case of the city of Marseilles (France) and inserted into a Decision Support System. With a more academic point of view, the model could serve as a cornerstone for the development of new models and methods for strategic issues in city logistics

A modeling approach for locating logistics platforms for fast parcels delivery in urban areas

International audienceThis study aims at defining a framework for optimizing, in a sustainable way (i.e. economical, eco-friendly and societal), the location of logistics platforms in urban areas. A first case study for our work is the city of Marseilles (France) which already has a logistics platform right in its centre (ARENC: 41362 m2 of warehouses and offices). In this abstract, we first provide a precise description of the problem we intend to solve. We then propose a mathematical model for representing it. Preliminary experimentations, based on the city of Marseilles, are then described; figures and preliminary results which are proposed for this first case study are obtained thanks to a decision-making software we have implemented. Conclusions and future works are finally drawn

The Multi Trip Vehicle Routing Problem with Time Windows and Release Dates

International audienceIn this paper the Multi Trip Vehicle Routing Problem with Time Windows and Release Dates is introduced. The problem is particularly interesting in the City Logistics context, where trucks deliver merchandise to depots located in the outskirts of the city. Goods continuously arrive during the day becoming available for final distribution after the working day has started. This introduces the concept of release dates associated with merchandise. In this paper, a set of instances is introduced and a hybrid genetic algorithm is proposed to solve the problem

Use of machine learning techniques to model wind damage to forests

This paper tested the ability of machine learning techniques, namely artificial neural networks and random forests, to predict the individual trees within a forest most at risk of damage in storms. Models based on these techniques were developed individually for both a small forest area containing a set of 29 permanent sample plots that were damaged in Storm Martin in December 1999, and from a much larger set of 235 forest inventory data damaged in Storm Klaus in January 2009. Both data sets are within the Landes de Gascogne Forest in Nouvelle Aquitaine, France. The models were tested both against the data from which they were developed, and against the data set from the other storm. For comparison with an earlier study using the same data, logistic regression models were also developed. In addition, the ability of machine learning techniques to substitute for a mechanistic wind damage risk model by training them with previous mechanistic model predictions was tested. All models were accurate at identifying whether trees would be damaged or not damaged but the random forests models were more accurate, had higher discriminatory power, and were almost totally unaffected by the removal of any individual input variable. However, if all information relating to a stand was removed the random forests model lost accuracy and discriminatory power. The other models were similarly affected by the removal of all site information but none of the models were affected by removal of all tree information, suggesting that damage in the Landes de Gascogne Forest occurs at stand scale and is not controlled by individual tree characteristics. The models developed with the large comprehensive database were also accurate in identifying damaged trees when applied to the small forest data damaged in the earlier storm. However, none of the models developed with the smaller forest data set could successfully discriminate between damaged and undamaged trees when applied across the whole landscape. All models were very successful in replicating the predictions of the mechanistic wind risk model and using them as a substitute for the mechanistic model predictions of critical wind speed did not affect the damage model results. Overall the results suggest that random forests provide a significant advantage over other statistical modelling techniques and the random forest models were found to be more robust in their predictions if all input variables were not available. In addition, the ability to replace the mechanistic wind damage model suggests that random forests could provide a powerful tool for damage risk assessment at the stand or single tree level over large regions and provide rapid assessment of the impact of different management strategies or be used in the development of optimised forest management with multiple objectives and constraints including the risk of wind damage

Observing the Forest Canopy with a New Ultra-Violet Compact Airborne Lidar

We have developed a new airborne UV lidar for the forest canopy and deployed it in the Landes forest (France). It is the first one that: (i) operates at 355 nm for emitting energetic pulses of 16 mJ at 20 Hz while fulfilling eye-safety regulations and (ii) is flown onboard an ultra-light airplane for enhanced flight flexibility. Laser footprints at ground level were 2.4 m wide for a flying altitude of 300 m. Three test areas of ∼500 × 500 m2 with Maritime pines of different ages were investigated. We used a threshold method adapted for this lidar to accurately extract from its waveforms detailed forest canopy vertical structure: canopy top, tree crown base and undergrowth heights. Good detection sensitivity enabled the observation of ground returns underneath the trees. Statistical and one-to-one comparisons with ground measurements by field foresters indicated a mean absolute accuracy of ∼1 m. Sensitivity tests on detection threshold showed the importance of signal to noise ratio and footprint size for a proper detection of the canopy vertical structure. This UV-lidar is intended for future innovative applications of simultaneous observation of forest canopy, laser-induced vegetation fluorescence and atmospheric aerosols

Genome-Wide Analysis of LIM Gene Family in Populus trichocarpa, Arabidopsis thaliana, and Oryza sativa

In Eukaryotes, LIM proteins act as developmental regulators in basic cellular processes such as regulating the transcription or organizing the cytoskeleton. The LIM domain protein family in plants has mainly been studied in sunflower and tobacco plants, where several of its members exhibit a specific pattern of expression in pollen. In this paper, we finely characterized in poplar six transcripts encoding these proteins. In Populus trichocarpa genome, the 12 LIM gene models identified all appear to be duplicated genes. In addition, we describe several new LIM domain proteins deduced from Arabidopsis and rice genomes, raising the number of LIM gene models to six for both species. Plant LIM genes have a core structure of four introns with highly conserved coding regions. We also identified new LIM domain proteins in several other species, and a phylogenetic analysis of plant LIM proteins reveals that they have undergone one or several duplication events during the evolution. We gathered several LIM protein members within new monophyletic groups. We propose to classify the plant LIM proteins into four groups: αLIM1, βLIM1, γLIM2, and δLIM2, subdivided according to their specificity to a taxonomic class and/or to their tissue-specific expression. Our investigation of the structure of the LIM domain proteins revealed that they contain many conserved motifs potentially involved in their function

Interpreting canopy development and physiology using the EUROPhen camera network at flux sites

Peer reviewe

La forêt vue du ciel: télédétection

Section 5 du Chapitre 3 "De la révolution sylvicole à l’industrie de demain: la place des nouvelles technologies dans les recherches forestières"National audienc