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Vers une économie circulaire forte : la méthodologie Design for Strong Sustainability© comme levier de transformation systémique et interdisciplinaire
No full textInternational audienceDepuis le rapport Brundtland (1987), la notion de développement durable s’estdéclinée en deux interprétations : la soutenabilité faible, qui postule une coexistenceharmonieuse entre croissance économique, équité sociale et préservation écologique, etla soutenabilité forte, qui exige le respect des limites planétaires et une justice socialeintégrale [1], [2], [3], [4]. Dans ce contexte, l’économie circulaire (EC) est souventprésentée comme une alternative durable à l’économie linéaire, promettant dedécoupler la consommation de ressources de la croissance économique. Pourtant,comme le souligne Franck Aggeri, les résultats concrets de l’EC restent décevants, enraison d’une prédominance de la circularité faible – une optimisation marginale des fluxde matières sans remise en cause des modèles économiques dominants [6]
Overcoming the Technical Hurdles of IoT Adoption: the FITNESS Project Vision and Insights
No full textWhite paper from the ANR-funded project NF-FITNESSThe Internet of Things (IoT) has emerged as a transformative force, enabling seamless connectivity and data exchange between diverse devices and networks. However, the realization of a truly interoperable, secure, and energy-efficient IoT ecosystem remains a significant challenge. In this paper, we present the vision and the first key findings of the FITNESS project, a comprehensive research initiative funded by the French Research Agency (ANR) as part of the France 2030 program. Our work aims to develop solutions that enable the IoT's full potential, emphasizing scalability, interoperability, security, and sustainability, and enabling seamless connectivity and efficient data transmission between diverse IoT devices and networks. We focus in this paper on three critical areas: IoT architecture and interoperability, the place of Artificial Intelligence in IoT, and energy efficiency. Additionally, we identify and analyze key use cases that demonstrate the practical applications of our research, highlighting the importance of real-world implementation to validate and refine our solutions. Through our dedicated research efforts, we have made significant advances across several key areas, while also laying the groundwork for further development in others. These contributions support the emergence of a more secure, efficient, and interoperable IoT ecosystem, and provide a foundation for adoption by stakeholders seeking to harness its transformative potential
Bayesian analysis of constrained Gaussian processes
No full textInternational audienceDue to their flexibility Gaussian processes are a well-known Bayesian framework for nonparametric function estimation. Integrating inequality constraints, such as monotonicity, convexity, and boundedness, into Gaussian process models significantly improves prediction accuracy and yields more realistic credible intervals in various real-world data applications. The Gaussian process approximation, originally proposed in [22] is considered. It satisfies interpolation conditions and handles a wide range of inequality constraints everywhere. Our contribution in this paper is threefold. First, we extend this approach to handle noisy observations and multiple, more general convex and non-convex constraints. Second, we propose new basis functions in order to extend the smoothness of sample paths to differentiability of class C^p , for any p ≥ 1. Third, we examine its behavior in specific scenarios such as monotonicity with flat regions and boundedness near lower and/or upper bounds. In that case, we show that, unlike the Maximum a posteriori (MAP) estimate, the mean a posteriori (mAP) estimate fails to capture flat regions. To address this issue, we propose incorporating multiple constraints, such as monotonicity with bounded slope constraints. According to the theoretical convergence and based on a variety of numerical experiments, the MAP estimate behaves well and outperforms the mAP estimate in terms of prediction accuracy. The performance of the proposed approach is confirmed through real-world data studies
A Hybrid Approach for Sustainable Marine Zoning Management Using Multi-agent Optimization and Negotiation Protocol
No full textInternational audienceMarine Spatial Planning seeks to manage ocean activities while balancing societal needs with environmental protection. However, conflicts arise because stakeholders often have divergent objectives and preferences that are not shared. These conflicts are interdependent, making centralized solutions challenging to implement effectively. This paper addresses this gap by introducing a novel conflict resolution framework within a cooperative Multi-Objective Multi-Agent System (MOMAS) for Marine Spatial Planning. Our approach combines heuristic-based negotiation mechanisms with memetic algorithms to derive Pareto-optimal solutions, promoting collaboration and reducing conflicts. The framework is tested using the Condorcet aggregation method to simulate negotiation scenarios. Results show a 20% increase in zoning efficiency and a 22% reduction in conflict, with statistical validation (p-value < 0.05) confirming these gains. Through case studies, we demonstrate the robustness of this approach and its potential to improve decision-making in marine spatial planning, yielding both environmental and economic benefits
Extending nanoindentation testing toward extreme strain rates and temperatures for probing materials evolution at the nanoscale
No full textInternational audienceFor the past 30 years, nanoindentation has provided critical insights into the microstructure–strength relationship for a wide range of materials. However, it has traditionally been limited to quasistatic testing at room temperature, which has hindered a holistic understanding of microstructurally induced deformation mechanisms and their dynamic evolution as a function of the temperature and strain rate. Over the past decade, the operational scope of nanoindentation has expanded dramatically. Temperatures up to 1100°C and strain rates as high as 10+4 s−1 and as low as 10−8 s−1 have become accessible. In addition, advanced techniques allow tracking microstructural evolution and corresponding changes in mechanical behavior during deformation under extreme conditions. These advancements have transformed nanoindentation into a versatile tool for comprehensive materials characterization, enabling high-throughput investigations under multimodal conditions
Sobriété numérique dans les PME : adoption et effets sur la performance globale
No full textNational audienc
Economie circulaire et intelligence artificielle : foisonnement d’innovations ?
No full textBlog Alternatives ÉconomiquesDepuis les travaux fondateurs de Joseph Schumpeter sur l’innovation, considérée comme étant une activité linéaire portée par un entrepreneur isolé, le concept d’innovation a considérablement évolué pour intégrer la dimension systémique des mécanismes à l’œuvre (Adatto et al., 2023). L’innovation systémique, bien qu’elle n’ait pas fait l’objet d’un consensus en ce qui concerne sa définition dans la littérature, se conçoit comme un concept qui englobe les multiples perspectives de l’innovation au sein d’un système complexe
Les Tissages de Charlieu : quand l’humanisme devient un levier de résilience au service de la souveraineté industrielle
No full textInternational audienc
Multi-line hybrid flow-shop scheduling problem with energy considerations
No full textInternational audienceThis article introduces a novel scheduling problem consisting of a multi-line hybrid flow-shop with energy considerations. The scheduling problem aims at optimising energy cost under time of use pricing structure with respect to production and energy-efficiency constraints. A 0–1 integer linear program based on a time-indexed formulation is proposed and allows to consider of variable power profiles for operations. Subsequently, a multi-start iterated local search-based heuristic is developed in order to address the resolution of large-scale instances. The performance of the proposed approaches is then assessed on randomly generated instances of various scales. Numerical experiments on an industrial case study also illustrate the economic benefits of considering a time of use pricing scheme with over 20% reduction in energy cost. Furthermore, it is demonstrated the importance of considering the system as a whole when considering energy in such a multi-line shop floor by examining three distinct optimisation strategies. Indeed, the benefits of a multi-line optimisation strategy compared to a sequential one are around 24% on average