Publications
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Towards a dynamic model of collective intelligence: Theoretical integration, nonverbal interaction and temporality
Most existing research on Collective Intelligence (CI) tends to emphasize final performance indicators or sums of individual cognitive traits, giving insufficient attention to how teams dynamically construct their collective capacity through ongoing interactions. In this paper, we propose an integrative perspective that draws on multiple existing approaches, ranging from conceptual frameworks (IMOI, TSM-CI) to measurement-oriented […]
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Augmented Perception: a real-time digital twin based approach to enhance robotic perception.
This paper introduces an Augmented Perception (AP) framework to enhance robotic perception in resilient manufacturing systems (MS) by integrating Digital Twin (DT) data directly at the sensor level in real time. Inspired by augmented reality, this approach enables robots to perceive both physical and virtual entities within a unified representation. To ensure real-time performance, we […]
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Graph-based framework for temporal human action recognition and segmentation in industrial context
Industry 5.0 places human operators at the center of industrial processes. In this context, analyzing human movements has become crucial for ensuring operator safety and improving productivity. More specifically, an accurate system for action recognition and segmentation is essential to identify and break down each action an operator performs. These systems enable a range of […]
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A game theory approach for optimizing job shop scheduling problems with transportation in common shared human–robot environments
The Job Shop Scheduling Problem with Transportation (JSSPT) is a critical challenge in modern industrial systems, particularly in environments where human operators and Autonomous Intelligent Vehicles (AIVs) interact. Traditional scheduling approaches often fail to address the dynamic and unpredictable nature of these shared human–robot environments. In response, this paper introduces a game theory-based scheduling algorithm […]
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Energy-Aware Optimization of Multi-Robot Systems with Task Allocation and Partial Recharge Scheduling
This paper presents a task allocation and scheduling model for multi-robot systems operating under energy constraints. The proposed model integrates key factors such as energy consumption, battery charging management, and task execution efficiency. To address this problem, we employ both an exact solver-based method and a bio-inspired algorithm, enabling a comparative analysis of their performance […]
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A New MILP Model for Supplier Selection: Improving Efficiency and Solution Quality under Risk
This paper contributes to the field of supplier selection under risk by proposing a Mixed Integer Linear Programming (MILP) model that integrates key decisionmaking factors such as cost and risk mitigation strategies. The proposed model offers a comprehensive approach for selecting the best supplier portfolio under uncertainty. Furthermore, the paper provides a detailed comparison of […]
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Pricing-Driven Optimization of Lot-Sizing and Scheduling in Hybrid Manufacturing-Remanufacturing Systems
The transition towards sustainable production models has intensified interest in hybrid manufacturing and remanufacturing systems, which play a crucial role in the circular economy. These systems integrate new production with the refurbishment of used products, presenting unique operational challenges. This paper examines the integration of pricing, scheduling, and lot-sizing in modern industrial operations, with a […]
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Towards efficient program execution on edge-cloud computing platforms
This paper investigates techniques dedicated to the performance of edge-cloud infrastructures and identifies the challenges to address to maximize their efficiency. Unlike traditional cloud-only processing, edge-cloud platforms meet the stringent requirements of real-time applications via additional computing resources close to the data source. Yet, due to numerous performance factors, it is a complex task to […]
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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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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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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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