Publications
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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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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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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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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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Multi-Agent Cooperative Camera-Based Semantic Grid Generation
The idea of cooperative perception for navigation assistance was introduced about a decade ago with the aim to increase safety on dangerous areas like intersections. In this context, roadside infrastructure appeared very recently to provide a new point of view of the scene. In this paper, we propose to combine the Vehicle-To-Vehicle (V2V) and Vehicle-To-Infrastructure […]
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A Hybrid Binary Grey Wolf Optimiser for WSN Deployment in Indoor Environments Based on BIM database
Wireless Sensor Networks (WSNs) represent a key component in smart building systems. An efficient WSN deployment involves selecting the most appropriate positions within the building to place sensors in order to maximize coverage and minimize the deployment cost. This paper proposes a novel approach called the Hybrid Binary GreyWolf Optimiser (HBGWO) to automate the WSN […]
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The impact of avatar embodiment in the context of virtual training environments
For the past few decades, protocols using immersive virtual reality to study human behavior have become increasingly more common. Indeed, the technology offers many new advantages that traditional experimental setups lacked (e.g., ecological validity). However, beyond its use as an experimental tool, experiments using VR have revealed new phenomena caused by the use of these […]
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DATA-DRIVEN PREDICTIVE ANALYSIS FOR CUTTING MACHINE FAILURES: A TECHNICAL REPORT ON RELIABILITY OPTIMIZATION
The prevention of recurring failures in modern manufacturing systems is of paramount importance for minimizing costs and downtime. Despite the potential for real-time data analysis using sensors offered by Industry 4.0 technologies, their widespread adoption, particularly among smaller manufacturing systems, remains a challenge. In response, this paper introduces an alternative approach to predictive maintenance planning, […]
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FVLLMONTI: The 3D Neural Network Compute Cube (N2C 2 ) Concept for Efficient Transformer Architectures Towards Speech-to-Speech Translation
This multi-partner-project contribution introduces the midway results of the Horizon 2020 FVLLMONTI project. In this project we develop a new and ultra-efficient class of ANN accelerators, the neural network compute cube (N 2C2), which is specifically designed to execute complex machine learning tasks in a 3D technology, in order to provide the high computing power […]
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Introducing the 3MT_French dataset to investigate the timing of public speaking judgements
In most public speaking datasets, judgements are given after watching the entire performance, or on thin slices randomly selected from the presentations, without focusing on the temporal location of these slices. This does not allow to investigate how people’s judgements develop over time during presentations. This contrasts with primacy and recency theories, which suggest that […]
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