Publications
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Digital Twin–Driven Multi-Objective Layout Optimisation of Flexible Robotic Cells with NSGA-II
Robotic cells in modern factories must be laid out for efficiency, flexibility, and fast adaptation to shifting product mixes [1]. Cycle time and safety hinge on where workstations, robot bases, stock bins, and tools sit, yet finding a balanced layout is challenging because static choices alter dynamic behaviour: moving a fixture a few centimetres can […]
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Autoconsommation et stockage thermique de l’énergie solaire dans une habitation résidentielle
L’objectif de ce travail est de tester des méthodes de gestion et de stockage des énergies renouvelables produites au niveau d’une habitation individuelle. Un simulateur, fondé sur les modèles des équipements d’une habitation et des sources d’énergies renouvelables solaire qu’elle intègre, a été conçu à des fins de développement d’algorithmes d’optimisation pour l’amélioration de la […]
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• A Multiobjective Optimization Model for Student Urban Carpool Hubs
Urban mobility is a growing challenge, particularly in some university environments where students face difficulties in commuting efficiently and sustainably. Among the various alternatives, carpooling has emerged as a promising solution to mitigate traffic congestion, transportation costs and environmental impacts. We propose, in this paper, a multi-objective optimization model considering spatial, behavioral, and environmental variables, […]
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Contribution à la caractérisation de l’affordance d’un environnement de travail industriel : une approche basée sur l’apprentissage profond combinant données réelles et synthétiques
Ce travail s’inscrit dans le cadre du projet “École De La Batterie”, dont l’un des objectifs concerne l’optimisation de la conception des postes de travail manuel dans le but d’améliorer leur ergonomie. Nos travaux s’inscrivent dans cette démarche et visent à caractériser l’affordance des éléments de ces environnements avec lesquels les opérateurs interagissent (outils, composants, […]
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GZSL-MoE: Apprentissage Généralisé Zéro-Shot basé sur le Mélange d’Experts pour la Segmentation Sémantique de Nuages de Points 3D Appliqué à un Jeu de Données d’Environnement de Collaboration Humain-Robot
Résumé L’approche d’apprentissage génératif zéro-shot ou zéro exemple de données (Generative Zero-Shot Learning, GZSL) a démontré un potentiel significatif dans les tâches de la segmentation sémantique de nuages de points 3D. GZSL approche exploite des modèles génératifs comme les GAN pour synthétiser des caractéristiques réalistes (caractéristiques réelles) des classes non vues. Cela permet au modèle […]
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From Individuals to Teams: A Conceptual Model for Group Behavior Integration in Industry 5.0
In Industry 5.0 environments, integrating human behavior models into scheduling and planning is essential. However, most research in this field focuses on individual modeling, overlooking the significant influence of group dynamics. Beyond isolated interactions, collective decisionmaking and team behaviors shape system performance, especially when deploying collaborative technologies such as Autonomous Intelligent Vehicles (AIVs) and smart […]
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JIT Organization Method for Sustainable and Integrated Production and Delivery Scheduling
This paper integrates sustainable production and delivery scheduling using a Just In Time approach to minimize delays and CO2 emissions in a job shop environment with hybrid vehicle fleets for the delivery. Beyond existing integrated production and delivery models, this work explicitly incorporates electric vehicle constraints, addressing energy consumption and charging requirements alongside scheduling decisions. […]
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Enhancing Industrial Process Optimization through Digital Twins
This paper explores the role of Digital Twins (DTs) in optimizing industrial processes, particularly in strategic sectors such as automotive, aerospace, and water treatment. With the growing need for companies to adapt to increased competition and technological advancements, DTs offer an innovative approach to process management. The study outlines the integration of real-time data analytics, […]
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Optimizing building envelope design across various French climates: A multi-objective approach using NSGA II and RMP method
Architects face a major challenge in designing buildings that enhance human comfort while minimizing energy consumption. To address this, the present work presents a novel multi-objective optimization approach, aiming to determine the optimal building envelope design. The developed approach focuses on minimizing energy consumption for both heating and cooling demand. Therefore, the methodology follows three […]
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Life Cycle Assessment of Vernacular Construction Techniques: Comparative Analysis of Tilestone Roofing vs. Conventional Systems
Traditional tilestone roofing, commonly used in UNESCO-listed French regions such as the Causses and Ce vennes, may provide notable sustainability benefits, yet comparative studies on roofing remain scarce. Previous research has highlighted the advantages of traditional construction, especially in wall systems: As reported by [1], up to a 91% reduction in embodied emissions with natural […]
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Impact of Successive Layer Spraying of Polymer Binder on Hygroscopic Performance of Earth Walls in Humid Tropical Environments
The use of earth in tropical building is gaining increasing attention due to its natural ability to regulate humidity, which is essential for thermal comfort. This study evaluates the hygroscopic performance of an earth wall stabilized with hemp fibers and a polymer binder, applied through successive layer spraying via gravity-driven impregnation—a technique borrowed from the […]
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Metaheuristic and Reinforcement Learning Techniques for Solving the Vehicle Routing Problem: A Literature Review
The Vehicle Routing Problem remains a pivotal challenge in combinatorial optimization, where the objective is to determine optimal routes for a fleet of vehicles serving geographically distributed customers under specific constraints. Over decades, a diverse spectrum of solution methodologies—spanning exact algorithms, heuristics, metaheuristics, and, more recently, machine learning—has emerged. This review critically examines the intersection […]