Publications
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An intelligent mechanism for energy consumption scheduling in smart buildings
In recent years, the incorporation of sensing technology into residential buildings has given rise to the concept of ”smart buildings”, aimed at enhancing resident comfort. These buildings are typically part of interconnected neighborhoods sharing common energy sources, which makes the energy consumption a critical consideration in decision-making processes. Consequently, optimizing energy usage in smart buildings […]
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Multi-Task Learning for PBFT Optimisation in permissioned Blockchains
Finance, supply chain, healthcare, and energy have an increasing demand for secure transactions and data exchange. Permissioned blockchains fulfilled this need thanks to the consensus protocol that ensures that participants agree on a common value. One of the most widely used protocols in private blockchains is the Practical Byzantine Fault Tolerance (PBFT) which tolerates up […]
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Apprentissage automatique d’EDPs contraintes par la physique pour l’identification des hétérogénéités dans les structures mécaniques élancées
On propose une méthode d’identification automatique d’EDPs hétérogènes en espace dont l’application visée est le contrôle non-destructif des structures mécaniques à partir de sollicitations en dynamique basse fréquence. Cette méthode reprend le principe d’approches récentes de construction automatique de modèles mathématiques en introduisant la possibilité d’intégrer des hétérogénéités en espace. Le problème d’identification résultant est […]
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Analyse de sensibilité du modèle énergétique d’un bâtiment pédagogique constitué de conteneurs maritimes
Les modèles énergétiques, bien que très utiles pour prédire le comportement physique du bâtiment, comportent des incertitudes (paramètres inconnus, approximations…). Ces incertitudes ont un impact sur la fiabilité des prédictions, qu’il est possible de limiter via la calibration du modèle. Nous présentons dans cet article une modélisation énergétique d’un bâtiment pédagogique construit à partir de […]
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Maximizing the number of satisfied charging demands of electric vehicles on identical chargers
This paper addresses the electric vehicle charging scheduling problem in a charging station with a limited overall power capacity and a limited number of chargers. Electric vehicle drivers submit their charging demands. Given the limited resources, these charging demands are either accepted or rejected and accepted demands must be satisfied. The objective of the scheduler […]
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Bus routing optimisation: a case study for the Toulouse metropolitan area
This paper investigates the efficiency evaluation of a public transport using an analysis of Origin-Destination matrices (mOD). The use of a trip-chaining method on the automatically collected transport data provides a realistic and accurate representation of traffic flows characterized by mOD. The introduction of a critical walking distance and an user flow at bus stop […]
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Simultaneous scheduling of production and maintenance in a flexible job-shop workshop
This paper proposes an integer linear program for joint and simultaneous scheduling of production and predictive maintenance tasks based on degradation prediction. The objective is to find a scheduling scheme that minimizes the total execution time while guaranteeing that the state of the machines is maintained below a predefined degradation threshold. Experiments are performed on […]
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Optimizing the flow of connected distribution logistics
Distribution and transport are considered to be key factors determining the quality of service and logistics costs, as they provide the connection between the different levels of the Supply Chain (SC). This study proposes a guideline to help industrial manufacturing companies manage their logistics distribution systems in an efficient and optimized way. The aim of […]
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Exploring the Capacitated Vehicle Routing Problem using the power of Machine Learning : A Literature Review
The Capacitated Vehicle Routing Problem is a classic logistics optimization challenge for which numerous approaches are employed to address it. A prevalent strategy involves employing machine learning for predicting demand, leveraging historical data to accurately forecast customer needs. Furthermore, reinforcement learning techniques are employed to optimize vehicle routes, adapting them dynamically in response to changing […]
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Flexible job-shop problem with predictive maintenance planning using genetic algorithm
The most common disruptions and emerging challenges that manufacturing systems frequently encounter include the arrival of new orders, last-minute order cancellations, unforeseen machine breakdowns, and alterations in due dates. To effectively respond to these challenges, production schedules are continually adjusted by implementing real-time rescheduling mechanisms that rely on up-to-the-minute data from the shop floor. This […]
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Personalisation in Mobility-as-a-Service: Where We Are and How to Move Forward
Within urban mobility ecosystem, Mobility-as-a-Service (MaaS) has come up as a promising approach to promote sustainable modes of transport and increase the attractiveness of public and shared multimodal mobility. It aims to become a viable alternative to personal cars for door-to-door trips. The long-term objective of MaaS is to change the people’s travel behaviour by […]
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Summer dataset of an operating education modular building
We propose a dataset concerning a modular education building (NR3) located on CESI Engineering School of Nanterre (Approximate GPS coordinates: 48.9033,2.1925). NR3 building is composed of 16 shipping containers offering an available surface of ≈220m² on two levels. It integrates 4 classrooms named Turing (38 m²), Tesla (51 m²), Nobel (38 m²) and Lumière (38 […]
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