Abstract—This paper studies train routing and scheduling problem for busy railway stations. The train routing problem is to assign each train to a route through the railway station and to a platform in the station. The train scheduling problem is to determine timing and ordering plans for all trains on the assigned train routes. Our objective is to allow trains to be routed in dense areas that are reaching saturation. Unlike traditional methods that allocate all resources to setup a route for a train until the route is freed, our work focuses on the use of resources as trains progress through the railway node. This technique allows a larger number of trains to be routed simultaneously in a railway node and thus reduces their current saturation. In this paper, we consider that trains can be coupled or decoupled and trains can pass through the railway station without stopping at any platform. To deal with this problem, this study proposes an abstract model and a mixed-integer linear programming formulation to solve it. The method is illustrated on a didactic example.

Le transport de marchandises integre un grand nombre de probleme d'optimisation tout au long de la chaine logistique. Cet article est dedie a la problematique de chargement/dechar-gement de containers dans un environnement portuaire. L'automatisation des processus est devenue une priorite pour les plus grands acteurs du secteur portuaire contraints de s'adapter a la croissance du volume de containers transportes liee a la globalisation de l'economie mon-diale et aux capacites des nouvelles generations de bateaux. La concurrence entre terminaux et la necessite de reduire les delais de chargement et dechargement des bateaux necessitent de la part des operateurs portuaires une augmentation de la productivite globale, une reduction des couts d'exploitation tout en garantissant une securite maximale. Cet article propose la description d'algorithmes qui permettent de trouver des solutions faisable pour le probleme de routage d'une flotte d'AGV, dans un temps raisonnable. La reso-lution exacte du probleme montre tres vite ses limites lors du passage a l'echelle. L'approche proposee ici est de coupler une resolution exacte avec des heuristiques. L'idee est de proposer des elements de solution dans le but de faire chuter la complexite intrinseque de ce type de probleme. Ainsi, une solution peut etre proposee avec un temps de resolution raisonnable vis a vis des contraintes imposees par les operateurs portuaires.

The management of rail traffic in stations requires careful scheduling to fit to the existing infrastructure, while avoiding conflicts between large numbers of trains and satisfying safety or business policy and objectives. The train scheduling and routing problem studied includes four tasks: scheduling, routing, platforming and conflict resolution. We propose a three-level decomposition method based on the interactional relationship among four tasks mentioned above to enhance the computational efficiency. This method is tested on full-day timetable obtained from a real-world station.

The real-time traffic management allows to solve unexpected disturbances that occur along a railway line during the normal development of the traffic. After a disturbance, the original timetable is restored through the rescheduling process. Despite the improvements of off-line decision support tools for trains dispatchers that enable a better use of rail infrastructure, real-time traffic management received a limited scientific attention. In this paper, we deal with the real time traffic management for regional railway networks, mainly single tracked, in which a centralized traffic control system is installed. The rescheduling problem is presented as a Mixed Integer Linear Programming Model which resolution allows to carry out the rescheduling process in a very short computational time.

This paper studies the problem of platforming trains faced by railway station infrastructure managers to generate a feasible conflict-free timetable. This platforming problem is to assign each train to an internal line inside the railway station and to find a path towards this line through the railway station network. Two kinds of movements are considered: commercial and technical movements. Strict reference arrival and departure times are only given for commercial movements by activity managers at a national level without any feasibility checking at the railway station level. On the other hand, a time deviation is permitted for technical movements. In this paper, we propose a sliding window algorithm using mathematical programming steps to solve the platforming problem. This hybrid algorithm consists of initialization, preprocessing, resolution, reinsertion and refinement. It takes into account train cancellation with suggestions for the modification of departure and arrival time of commercial movements in order to minimize the number of cancellations. The algorithm is tested based on real data related to a French railway station.

This paper studies a train routing and scheduling problem faced by railway station infrastructure managers to generate a conflict-free timetable which consists of two parts, commercial movements and technical movements. Firstly, we present the problem and propose a discrete-time mixed-integer linear mathematical model formulation. Due to the computational complexity of integer programming methods, we need to improve the calculation performance. On one hand, we consider the problem in continuous-time domain which decrease the computational size. The integrality of the scheduling variables is proved. On the other hand, the redundant constraints are cut off by probing the potential conflicts between trains and movements. The full practical problem is large: 247 trains consisting of 503 movements per day should be considered. The proposed approach can solve an instance made of 60 trains and 121 movements representing 385 minutes of traffic within less than 2 minutes.

The real-time traffic management allow to solve unexpected disturbances that occur along a railway line during the normal developement of the traffic. The original timetable is restored through the rescheduling process. Despite the increase of real-time decision support tools for trains dispatchers that enable a better use of rail infrastructure, real-time traffic management received a limited scientific attention. In this paper, we deal with the real time traffic management for regional railway networks, mainly single tracks, in which a centralized traffic control system is installed. The rescheduling problem is presented as a Mixed Integer Linear Programming Model which resolution allows to carry out the rescheduling process in a very short computational time.

Conventional architectures based on a central servers are not suitable and cannot scale well in a distributed and high dynamic computing enviroment. Futuristic ubiquitous landscape requires the development of robust, reliable and flexible distributed information systems capable of large scaling and supporting the large amount of simultaneous user requests. In this paper, we propose an innovative information system based on intelligent agents, which is capable of optimizing the search task and managing the services within a coalition of intelligent agents. Users will request a set of information services provided by information providers distributed among a Big Data Network (BDN). The system is divided into two subsystems. The first subsystem is responsible for the search optimization task using an evolutionary algorithm. It generates optimized Workpans for mobile agents that collect needed data from the BDN. The scond subsystem is composed of coalitions of peer agents whitch are endowed with the ability of role switching. A peer agent is by default a passive agent (client), once it receives a given service it can switch its role to become an active agent (service provider) for a given period of time. We provide in the end of this paper simulations supporting our claims about role switching performances and statistical results about the coalition of agents before and after role switching.

Timed Petri Nets are a good modeling framework to express the behavior of discrete event systems, such as transport or manufacturing systems. They allow to represent easily the distribution of tasks within a complex system, with the capacity to handle time constraints on the duration of these tasks.

In this paper, we propose to use a constraint programming approach to address the reachability problem in Timed Petri Nets (TPNs). TPNs can be used to model a wide class of systems, from manufacturing issues to formal verification of embedded systems. Many of the considered problems can be modeled as reachability problems in TPNs. To reduce the space state explosion brought by the exploration of the TPN behavior, we propose to follow the incremental methodology proposed by Bourdeaud'huy and Hanafi (2006), who translate the reachability graph of Timed PNs into a mathematical model. We improve this model by adding valid inequalities and search for solutions using Constraint Programming (CP). More particularly, we compare different labeling strategies and assess their respective efficiency.

Les entites de l'Intelligence Artificielle, communiquantes avec leur entourage, telles que les PDAs, les telephones, les capteurs, les robots, les logiciels, les middlewares, etc. sont de plus en plus presentes dans notre environnement. La nouvelle topographie de nos espaces quotidiens introduit les notions de l'Intelligence Artificielle Distribuee, l'Intelligence Ambiante et l'Informatique Ubiquitaire. Notre objectif est d'avoir un acces en temps reel, via un support mobile, a differents types d'information issus d'un environnement ubiquitaire, tels que les lieux touristiques et les horaires de bus. Dans ce papier, nous proposons une architecture efficiente d'un systeme ubiquitaire cible base sur une approche multi-agent. Nous nous focalisons dans notre etude sur le Grand Stade Lille Metropole et les services qui peuvent y etre demandes. L'architecture proposee va devoir supporter les services et optimiser leur qualite par rapport au temps de reponse et au cout de l'information.

In this paper, we are interested in finding efficient practical approaches to solve the Container Stacking Problem in Maritime Ports. Given container arrivals in a container port terminal, the objective is to assign a slot to each one in a storage area at least cost with respect to pre-defined constraints. The cost is expressed in term of number of expected relocation movements. The constraints to respect are stack height, stack number, and departure dates. We propose to improve a previous heuristic model proposed by Mark B. Duinkerken and Ottjes (2001) based on the computation of an indactor called the “remaining stack capacity“.

This paper is part of an original approach of mathematical modeling for solving cyclic scheduling problems. More precisely, we consider the cyclic job shop. This kind of manufacturing systems is well fitted to medium and large production demands. Many methods have been proposed to solve the cyclic scheduling problem. Among them, we chose the exact techniques, and we focus on the mathematical programming approach. We proposed, in an earlier study, a mathematical programming model for cyclic scheduling with Work-In-Process minimization. We propose here several cutting techniques to improve the practical performances of the model resolution. Some numerical experiments are used to assess the relevance of our propositions. We made a comparison between the original mathematical model and the one endowed by the proposed cuts. This comparison is based on a set of benchmarks generated for this reason. In addition, we make another comparison based on some examples from the literature.

In this article, we focus on the transient inter-production scheduling problem between two cyclic productions in the framework of flexible manufacturing systems. This problem is first formulated as a reachability problem in timed Petri nets (TPN), then solved using a methodology based on constraint programming. Our work is based on the controlled executions proposed by Chretienne to model the sequence of transition firing dates. Our methodology is based on a preliminary resolution of the state equation between initial and final states in the underlying non-TPN. Then, we choose a duration T-max corresponding to the maximal duration time of the scheduling. For each solution S of the state equation, we build a controlled execution from the sequence of firings in S. After the propagation of firing date constraints and reachability constraints in the TPN, we use constraint programming to enumerate the set of feasible controlled executions.

The European Union set up a European management system for rail traffic: the ERTMS system to ensure, in full safety, train circulation on different European networks. As the full deployment of this system is long and expensive, evolutions are necessary and raise other technological challenges. The goal is to determine how to use ERTMS specifications to produce test scenarios. This paper presents methods, models and tools dedicated to the generation of test scenarios for the validation of ERTMS components based on functional requirements.

Distributed Discrete Event Systems (Distributed DES) are increasing with the development of networks. A major problem of these systems is the evaluation of their performance at the design stage. We are particularly interested in assessing the impact of computer networking protocols on the control of manufacturing systems. In our design methodology, these systems are modeled using Petri nets. In this context, we propose an approach to modeling network protocols based on Oriented Object Petri Nets. Our ultimate objective is to assess by means of simulations the performances of such a system when one distributes their control models on an operational architecture. In this study, we are implementing a component based approach designed to encourage reuse when modeling new network protocols. To illustrate our approach and its reuse capabilities, we will implement it to model the link layer protocols of the norms IEEE 802.11b and IEEE 802.3.

In this paper, we propose a mathematical programming model for the resolution of the reachability problem in Time Petri Nets. We are more particularly interested in unweighted Time Petri Nets with safe markings and weak time semantics.

The evaluation of using distributed systems DS in place of centralized systems has introduced the distribution of many services and applications over the network. However, this distribution has produced some problems such as the impacts of underlying networking protocols over the distributed applications and the control of the resources. In this paper we are interested particularly in manufacturing systems. Manufacturing systems are a class of distributed discrete event systems. These systems use the local industrial network to control the system. Several approaches are proposed to model such systems. However, most of these approaches are centralized models that do not take into account the underlying network. In this context, we propose the modeling of the distributed services and the underlying protocols with High-Level Petri Nets. Since the model is large, complex and therefore difficult to modify, we propose a component-based modeling approach. This approach allows the reuse of ready-to-use components in new models, which reduces the cost of development. To illustrate our approach and its reuse capabilities, we will implement it to model the link layer protocols of the norms IEEE 802.11b and IEEE802.3