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Heuristics are important techniques designed to find quickly good feasible solutions for hard integer programs. Most heuristics depend on a solution of the relaxed linear program. Another approach based on Lagrangian relaxation offers a number of advantages over linear programming, namely it is extremely fast for solving large problems. Wedelin heuristic is such a Lagrangian based heuristic, initially developed to solve airline crew scheduling problems. The performance of this method depends crucially on the choice of its numerous parameters. To adjust them and learn which ones have important influence on whether a solution is found and its quality, we propose to conduct a sensitivity analysis followed by an automatic tuning of the most influential parameters. We have implemented a C++ open-source solver called baryonyx which is a parallel version of a (generalized) Wedelin heuristic. We used the Morris method to find useful continuous parameters. Once found, we fixed other parameters and let a genetic optimization algorithm using derivatives adjust the useful ones in order to get the best solutions for a given time limit and training instance set. Our experimental results done mostly on crew and bus driver scheduling benchmarks tackled as set partitioning problems show the significant improvements obtained by tuning the parameters and the good performances of our approach compared to state-of-the-art exact and inexact integer programming solvers.

National audience; D. helianthi causes phomopsis stem canker. Ascospores infect sunflower leaves, which will generate killing girdling symptomps. After harvest, fungus mycelium survives on infected stubble. At the end of winter, D. helianthi perithecia appear and will release ascospores. Disease management relies on cultural, genetic and chemical control methods. Fungicide treatments have to be applied just before the main ascospore showers. Farmers and advisers therefore need a Decision Support System to predict these periods. This communication presents the adaptation of the generic SimMat model to D. helianthi to fulfill this need.; Diaporthe helianthi est l’agent causal du phomopsis du tournesol. Les ascospores infectent les feuilles, qui vont générer des taches encerclantes mortelles. Après récolte, le mycélium survit sur les résidus. A la fin de l’hiver, des perithèces apparaissent et vont émettre des ascospores de D. helianthi. Les principales méthodes de gestion sont agronomique, génétique, et chimique. Pour qu’ils soient efficaces, les traitements fongicides doivent coincider avec la première émission significative d’ascospores. Les agriculteurs ont donc besoin d’un outil d’aide à la décision prédisant la temporalité des émissions des ascospores. Cette communication présente l’adaptation du modèle générique SimMat répondant à ce besoin.

International audience; This work deals with the simulation of spatial complex systems resolved with cellular models. We compare two component-based modeling implementations, based on DSDE and Multicomponent formalisms, using a Virtual Laboratory Environment framework (VLE) that is based on the DSDE formalism.

National audience

Diaporthe helianthi est l’agent causal du phomopsis du tournesol. Les ascospores infectent les feuilles, qui vont générer des taches encerclantes mortelles. Après récolte, le mycélium survit sur les résidus. A la fin de l’hiver, des perithèces apparaissent et vont émettre des ascospores de D. helianthi. Les principales méthodes de gestion sont agronomique, génétique, et chimique. Pour qu’ils soient efficaces, les traitements fongicides doivent coincider avec la première émission significative d’ascospores. Les agriculteurs ont donc besoin d’un outil d’aide à la décision prédisant la temporalité des émissions des ascospores. Cette communication présente l’adaptation du modèle générique SimMat répondant à ce besoin., D. helianthi causes phomopsis stem canker. Ascospores infect sunflower leaves, which will generate killing girdling symptomps. After harvest, fungus mycelium survives on infected stubble. At the end of winter, D. helianthi perithecia appear and will release ascospores. Disease management relies on cultural, genetic and chemical control methods. Fungicide treatments have to be applied just before the main ascospore showers. Farmers and advisers therefore need a Decision Support System to predict these periods. This communication presents the adaptation of the generic SimMat model to D. helianthi to fulfill this need.

Rubrique : Données - Informatique - I.A. - IHM; Le réseau RED organise la première édition des Journées DEVS Francophones (JDF). RED a pour but de développer, fédérer et promouvoir les travaux autour de la théorie de la modélisation et de la simulation, et plus particulièrement autour du formalisme DEVS et de ses extensions. L’objectif est de promouvoir une approche systémique et intégrée de la modélisation des systèmes complexes. Les principaux thèmes du réseau sont :- l’ingénierie des modèles ;- la validation et la certification des simulateurs ;- la performance des simulateurs ;- la validation et la vérification des modèles.

Mixed fruit-vegetable cropping systems (MFVCS) are a promising way of ensuring environmentally sustainable agricultural production systems in response to the challenge of being able to fulfill local market requirements. Indeed, they combine productions and they also make a better use of biodiversity. These agroforestry systems are based on a complex set of interactions modifying the utilization of light, water and nutrients. Thus, designing such a system must optimize the use of these resources, by maximizing positive interactions (facilitation) and minimizing negative ones (competition). To attain these objectives, the system's design has to include the spatial and temporal dimensions of these interactions, taking into account the evolution of above- and belowground interactions over a time horizon. However, a considerable amount of research has been conducted, on the one hand, to prove the interest of agroforestry, and on the other hand to propose models supporting cropping plan and crop rotation decisions, but to our knowledge, no model supports the spatial and temporal allocation of both vegetable crops and trees in agroforestry systems. Therefore, we initially built a first MFVCS prototype using the Weighted Constraint Satisfaction framework but the resolution was limited to small scale systems. In this paper, we explore larger MFVCS models using a solver based on Integer Quadratic Programming. The limits of exact methods in solving the MFVCS problem are presented showing the need for approximation methods able to solve a large scale system with solutions of good quality in reasonable time, which could be used in interactive design with farmers and advisers.

The study of information dissemination phenomena of large-scale is a new field. Diffusion of information is defined as the communication process by which an idea or information spreads within a social system and that can impact the behaviour of individuals. Institutions and firms search to understand and predict the impact of information propagation on individuals. Agent-based modelling is a powerful approach for studying such a collective process. However, existing models oversimplify adopters' cultural attributes, different type of link and information content, despite the evidence of their central role in diffusion process. In this thesis, we challenge the feasibility and utility of a more realistic representation of population. We use the DEVS formalism, extended by DS-DEVS and PDEVS in order to simulate the propagation phenomena within a multi-layer social network (MSN)., L’étude des phénomènes de la diffusion d’information à grand échelle est un domaine récent. La diffusion d’information est définie comme le processus de communication par lequel une idée ou une information se propage dans une population et qui peut impacter le comportement des individus. Les institutions, tout comme les entreprises, cherchent à comprendre et à prévoir l’impact de la propagation d’information sur les individus. Une approche de modélisation et simulation permet de mieux comprendre ce processus social et de répondre à ces questions. La modélisation et la simulation à base d’agents offre une approche puissante pour modéliser un tel processus social. Toutefois, les modèles actuels simplifient fortement les facteurs culturels et les informations représentées dans le modèle ainsi que les différents liens interconnectant les individus. Ces éléments sont centraux et déterminants pour le processus de propagation. Afin d'améliorer les modèles de propagation, nous explorons dans cette thèse une représentation de la population plus réaliste. Nous proposons une architecture de modélisation et simulation permettant de simuler les phénomènes de propagation au sein des réseaux sociaux multiplexes et dynamiques basée sur le formalisme DEVS.