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International audience; Transportation engineering, and especially of Dangerous Goods (DG), is one of the areas in which technological development is crucial. Logistic control systems, routing and scheduling algorithms, supply chain management have been applied in this aspect so as to improve the cost-effectiveness ratio and to reduce risks. Unfortunately, most of these works remain theoretical since tests on real case scenario sometimes proves difficult to achieve especially when we are dealing with Dangerous Goods Transport (DGT). In this paper, an architecture of a visual DGT simulation system has been introduced. It provides entries for testing these works and produces results close to real experiments. Applications on serious games, financial market, engineering are evidence of success of the visual simulation system. Thus, the challenge consists on how to design a system that represents real-world systems with an appropriate degree of complexity and dynamics. Several researchers have already suggested solutions since the 50s. These solutions have been classified in three levels: microscopic, mesoscopic and macroscopic simulation. It has been decided to use a microscopic approach using an agent-based model. It allows the representation of systems at different levels of complexity, a System of Systems (SoS), through the use of autonomous, goal-driven and interacting entities. The system is implemented using the software MATSim (http://www.matsim.org/). The main actors of the system stand for the DG Carriers Operator (CO) agent that manages a fleet of DG Carriers agents, taking logistic decisions on their behalf. The COs collaborate with the National Authority (NA), which is an agent concerned by the safety shipment of goods at regional and national level. The paper focus on the Multi-Agent System (MAS) architecture and introduces its key components as well as the means on interaction.

International audience; In this paper, an original ranking operator is introduced for Triangular Fuzzy Numbers. The purpose is to elaborate fast and efficient algorithms dealing with complicated operations and big data in fuzzy decision-making. The proposed ranking operator takes advantage of the topological relationship of two triangles, besides the Inclusion Index concept -- which is an index indicating the Degree of Inclusion in the MIN of two Fuzzy Numbers, a way to approach the "strongly included in". Consequently, the ranking result can mostly be deduced directly, allowing an efficient ranking process.

This paper proposes a general trajectory's meta-model and its architecture. In order to provide a unified meta-model and a powerful framework for trajectory's services and queries, the proposed trajectory's data-model has benefited from advantages of both conceptual and ontological space-time. However, it extends the basic data-model of trajectory with new patterns as Space Time Path to describe activities of the moving object, and Composite Region of Interest. Additionally, the proposed system is distinguished by providing framework for dealing moving objects trajectory, in an interoperable way, using heterogonous sensors that traditional data model alone are incapable for this purpose. The proposed system architecture for moving object trajectory's data-model is focused on service composability and data interoperability combining OGC standards, Service-Oriented Architecture and streaming technology, to allow applications constructed using the framework have better performance.

This chapter describes a real-time mobile information system which responds to the vulnerabilities of the transportation of dangerous goods. It describes the integration of various software components to boost HazMat (hazardous material) telegeomonitoring and presents a real-time, object-oriented model. It also explains how to integrate a spatial decision support system and how the result can be exploited by computer science. It focuses specifically on two particularly helpful contributions to improvements in the safe transport of HazMat. The first is the problem of finding the fuzzy shortest path. It discusses an original solution using an algebraic dioid structure to solve the k-best fuzzy shortest paths problem. The second deals with mobile object modelling. A mobile object data model and a mobile query language with a powerful set of spatiotemporal predicates are outlined. This approach is based on the comprehensive framework of abstract data types. It represents the first steps in constructing innovative moving object databases.

In modern container terminals, efficiently managing the transit of the containers becomes more and more of a challenge. Due to the progressive evolution of container transport, traffic management within container ports is still an evolving problem. To provide adequate strategy for the increased traffic, ports must either expand facilities or improve efficiency of operations. In investigating ways in which ports can improve efficiency, this paper proposes a Markov Decision Process (MDP) for loading and unloading operations within a container terminal. The proposed methodology allows an easy modeling for optimizing complex sequences of decisions that are to be undertaken at each time. The goal is to minimize the total waiting time of quay cranes and vehicles, which are allocated to service a containership. In this paper, reinforcement learning, which consists of solving learning problems by studying the system through mathematical analysis or computational experiments, is considered to be the most adequate approach.

Association rule discovering is one of the most important procedures in data mining. Lattice theory paradigm has been successfully used for the association rule mining. In particular, the theoretical foundation based on the field of Galois lattice has been used in the design of efficient algorithm for mining the frequent itemsets in transactional database. In this paper we describe a formal framework for the problem of mining closed frequent itemsets, where theoretical foundation is based on the algebraic topology. By means of Q-analysis and according to intrinsic q-values, an approximative closed frequent itemsets can be extracted. In data mining process, a large number of association rules are discovered. In this paper we also show how the algebraic topology-theoretic framework can be used to organize association rules by means of metarules.

In shipping port sector, containers are the most dynamic and complex to manage. To provide adequate strategy for the increasing traffic, ports must either expand facilities or improve efficiency of operations. In investigating ways in which ports can improve efficiency, this paper outlines a container terminal simulation model and gives components architecture that are implemented with Java. Simulator calibration and validation are also presented in the paper. The main goal of the present work is to provide a help tool in a port decision support system. The object oriented software design using UML diagrams is deployed in this project.

Spatial data mining fulfils real needs of many geomatic applications. It allows the geomatics community to take advantage of the growing availability of geographically referenced data and benefit from this rich information resource. This article addresses spatial data classification for using decision trees. A new method called SCART which differs from conventional decision trees by considering the specifics of geographical data, namely their organisation in thematic layers, and their spatial relationships is proposed. SCART is an extension of CART methods in two ways. On the one hand, the algorithm considers several thematic layers as in the so-called relational data mining area, and on the other hand, it extends discriminating criteria to address concerns about the neighbourhood. As such, the algorithm determines which combination of attribute values and spatial relationships of neighbouring objects provide the best criterion.

The concept of Environmental Information Systems (EIS) emerged from the concerns and the efforts carried on by world wide private and official organisations in order to promote an effective use of environmental data. These data are of various natures such as statistics, thematic maps, or documents describing the identification and the quantification of the environmental resources. The Environmental Information Systems became institutional tools providing pragmatic solutions for sustainable development in various fields. The objective of an EIS is to increase the quality and the efficiency in the decision-making process. To achieve this goal, the EIS requires the integration of various information processing technologies: Geographical Information Systems (GIS); Database Management Systems (DBMS); Space Imagery; Decision Support Systems (DSS); etc. However, the implementation of such an integration generates new requirements, namely data interoperability, data description by metadata, reverse engineering from existing applications and remote data access and data processing. This leads to the reconsideration of the analysis and design methodology.

The spatial network constitutes an essential support for the spatial organisation of the territory, where accessibility plays a key role in transportation dynamics. In fact, it is dependent on the transportation network quality and place structure; it influences our daily moving and our mobility decisions. In this paper we adopt the fuzzy spatial network Voronoi diagram (fuzzy-SNVD), an approach based on fuzzy arithmetic and graph theory, in order to evaluate the fuzzy Voronoi geographical accessibility to its generators (station, public facility, equipment, etc.). This evaluation and its cartographic representation occupy a key position among the necessary tools which can give decision makers effective assistance support in the transport planning process. Indeed, we propose within this framework two algorithms which allow calculating the fuzzy-SNVD and which consist in assigning each Voronoi generator to its closer nodes of the graph modelling a real spatial network. This assignment of the nodes is based on the comparison of the weights of the shortest traversed paths, which are considered fuzzy numbers representing, in a way more faithful to reality, the travel times, speeds or all values describing moving on the transport network.