Publications
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Dynamic Integrated Production and Delivery Scheduling with Electric Vehicles: A Hybrid Ant Colony System Approach
This paper addresses a dynamic Integrated Production and Delivery Problem (IPDP), where customer orders arrive in real time and production and transportation decisions must be continuously updated. To manage this dynamic envi- ronment, we develop D-HACS, a Dynamic-Hybrid Ant Colony System that adapts integrated schedules as new information becomes available. Computational experiments show that D- […]
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Energy-Aware Flexible Flow Shop Scheduling with Solar PV, Battery Storage, and Demand Response: A Genetic Algorithm Approach
Green manufacturing increasingly requires pro- duction systems to balance operational performance with en- ergy efficiency and cost-effectiveness. This paper addresses an energy-aware flexible flow shop scheduling problem in which a factory operates under a time-of-use electricity tariff, participates in a demand response reward program, exploits on- site photovoltaic generation, battery energy storage, and applies an […]
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Culture organisationnelle et mobilité durable : une approche méthodologique en contexte universitaire
Face au changement climatique, les établissements d’enseignement supérieur jouent un rôle clé dans la promotion de comportements durables. Cette étude explore l’impact de la culture organisationnelle sur les choix de transport des étudiants. Pour ce faire, une enquête a été menée auprès de 294 étudiants en mastère spécialisé au CESI, entre février et mai 2024. […]
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Multi-objective optimization of artificial neural networks using Fast NSGA-II for electricity demand forecasting
Accurate short-term electricity demand forecasting is a critical requirement for modern power systems, as forecast errors directly affect generation scheduling, market prices, and operational costs, particularly under dynamic pricing environments and increasing demand volatility. This study proposes an integrated forecasting framework combining Artificial Neural Networks (ANNs) with Multi-Objective Optimization (MOO) to jointly improve predictive accuracy […]
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Fault Tolerant Control of a 4 Wheels Driven Steer by Wire Electric Vehicle: Case of Active Front Steering Faults
This paper presents an Active Fault-Tolerant Control strategy for a four-wheel-drive electric vehicle equipped with in-wheel motors and a Steer-by-Wire system with Active Front Steering. A nonlinear full-vehicle dynamic model is developed, incorporating vertical, lateral, longitudinal, wheel, and tire–road interaction dynamics. A multi-layer Global Chassis Control architecture is designed to simultaneously ensure vehicle stability, maneuverability, […]
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BIM-LPS® Integration Case Study in the MEP Sector: Automating Phase Schedule Generation
Abstract – The Last Planner System® (LPS®) and Building Information Modeling (BIM) hold strong potential to improve construction productivity, yet their integration at the dataprocessing level remains limited. Information embedded in BIM models is often insufficiently structured and therefore not directly exploitable for LPS® implementation. This study proposes an approach that integrates LPS® with BIM […]
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Bi-Objective Electric Vehicle Charging Scheduling Under Stochastic Charging Durations
This paper addresses the electric vehicle charging scheduling problem under stochastic charging durations, where uncertainty arises from variations in actual charging times that are typically assumed deterministic in existing literature. We formulate a bi-objective optimization problem minimizing the expected values of peak load and total tardiness. We explicitly enforce non-overlapping charging sessions within the objective […]
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ResGNN: a residual GNN approach for leveraging general user preferences in session-based recommender systems
In recent years, session-based recommender systems (SBRSs) have emerged as pioneers for intelligent recommendation environments by capturing short-term user preferences without requiring direct access to user history. However, the challenge remains in effectively considering both short-term and long-term user preferences. Graph neural networks (GNNs) have shown promise in this field by leveraging the structural information […]
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Advanced PV-enabled heat generation system with precise thermal power regulation
This study presents an advanced PV-enabled heat generation system with precise thermal power regulation for resistive heating applications. Conventional solar thermal systems often rely on direct PV–resistor coupling, which leads to poor energy utilization, or MPPT-based operation, which maximizes electrical extraction but provides limited control over chamber temperature. To address these limitations, the proposed system […]
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Toward Seamless Human-Robot Collaboration: VR-Enhanced Teleoperation with Transparent Shared Control
Shared control is widely used in robotic telemanipulation to combine human input with autonomous assistance. However, assis- tive behaviors are often embedded within the control loop and remain difficult for operators to interpret, leading to potential misalignment be- tween user intent and system response. To resolve this misalignment, we propose an immersive teleoperation system based […]
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Strength, repairability, and debonding of vitrimer structural adhesive joints
Introduction: Debondable and repairable epoxy-based vitrimer adhesives offer a sustainable solution to conventional epoxy adhesives for structural applications. This study evaluated the performance of a vitrimer adhesive in structural single-lap-bonded joints and investigated its repairability and debonding characteristics in comparison with those of a conventional epoxy adhesive. Materials and methods: Metal substrates, aluminum (Al6061) and […]
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LOOPER: A framework for synthetic dataset generation with configurable sensors and multi-view XR environments
Collecting multi-view datasets is essential for training and evaluating AI models in domains such as robotics and autonomous systems. However, generating such datasets remains challenging due to sensor synchronization issues and the labeling process, which is often timeconsuming, error-prone, and dependent on manual intervention. To address these limitations, a novel framework, LOOPER (Light Object and […]