Publications
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Integration of Pricing and Production Scheduling Decisions: A Mathematical Model
In today’s competitive manufacturing landscape, achieving operational efficiency and optimizing revenue generation are key objectives for make-to-order manufacturers. This paper presents a novel approach for integrating production scheduling and pricing decisions in a make-to-order manufacturing environment. We propose a comprehensive mathematical model that addresses the complex interplay between production scheduling and pricing strategies. By jointly […]
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Evolutionary-Based Ant System Algorithm to Solve the Dynamic Electric Vehicle Routing Problem
This article addresses the Dynamic Electric Vehicle Routing Problem with TimeWindows (DEVRPTW) using a hybrid approach blending genetic and Ant Colony Optimization (ACO) algorithms. It employs an Ant System algorithm (AS) with an integrated memory system that undergoes mutations for solution diversification. Testing on Schneider instances under static and dynamic conditions, with run time of […]
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Elevating Manufacturing Excellence: A Data-Driven Approach to Optimize Overall Equipment Effectiveness (OEE) for a Single Machine
In the intensely competitive landscape of global manufacturing, achieving operational excellence is paramount for survival and success. Central to this endeavor is the optimization of Overall Equipment Effectiveness (OEE), a key metric that directly influences resource efficiency and product quality. Manufacturing companies face numerous challenges, including maintenance inefficiencies, unplanned downtimes, and product quality variations, which […]
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Raw dataset of compression tests on a vegetable oil-based polyurethane foam exposed to different ageing conditions
The current dataset brings raw compression test information of a vegetable-based polyurethane foam (PUF) exposed to different temperatures over different periods of time. Such experimental dataset can provide researchers with important information in the application of numerical and data-driven simulations. Also, it saves money and time once the experimental part is already available. At total, […]
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An Overview of Artificial Intelligence Driven Li-Ion Battery State Estimation
The omnipresence of batteries in nowadays appliances such as portable devices, electrical vehicles, hybrid microgrids, etc. gives them a special priority in energy storage. In addition, the high cost of battery manufacturing makes the maintenance and the monitoring of their states critical. The state estimation is a complicated process that may include many parameters to […]
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Development and Evolution of Hybrid Microgrids in the context of Contemporary Applications
This chapter provides a valuable insight to the development and evolution of hybrid microgrids, their applications, energy demand analysis, energy sources, mathematical modeling, objective parameters, and case studies. It begins with the definition of hybrid microgrids and highlights their importance in various sectors. Onward, it discusses the key microgrid applications. The analysis of energy demand […]
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Photogrammetry and deep learning for energy production prediction and building-integrated photovoltaics decarbonization
Building-Integrated photovoltaics (BIPV) have emerged as a promising sustainable energy solution, relying on accurate energy production predictions and effective decarbonization strategies for efficient deployment. This paper presents a novel approach that combines photogrammetry and deep learning techniques to address the problem of BIPV decarbonization. The method is called BIM-AITIZATION referring to the integration of BIM […]
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A Systematic Review of Predictive Maintenance and Production Scheduling Methodologies with PRISMA Approach
Predictive maintenance has been considered fundamental in industrial applications over the last few years. It contributes to improving reliability, availability, and maintainability of the systems and decreasing production efficiency in manufacturing plants. This article aims to explore the integration of predictive maintenance into production scheduling through a systematic review of literature. The review includes 165 […]
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EEG-based Schizophrenia Classification using Penalized Sequential Dictionary Learning in the Context of Mobile Healthcare
Mobile healthcare is an appealing approach based on the Internet of Medical Things (IoMT) and cloud computing. It can lead to unobstructed, economical, and patient-centric healthcare solutions. The key performance indicators of such systems are dimensionality reduction, computational effective- ness, low latency, and accuracy. In this context, a novel approach is devised for EEG-based schizophrenia, […]
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Développement d’une nouvelle méthode numérique basée sur l’arithmétique des intervalles pour la reconstruction de matrice Origine/Destination
La matrice Origine/Destination (OD) revêt une importance capitale dans le dimensionnement et la planification d’un système de transport. L’estimation des matrices OD est principalement réalisée par les gestionnaires de réseau à partir de données issues d’enquêtes. Le déploiement massif d’outils numériques permet l’acquisition automatique de données en temps réel comme la billettique. Il génère une […]
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Resource-Constrained EXtended Reality Operated With Digital Twin in Industrial Internet of Things
EXtended Reality (XR) alongside the Digital Twin (DT) in Industrial Internet of Things (IIoT) emerges as a promising next-generation technology. Its diverse applications hod the potential to revolutionize multiple facets of Industry 4.0 and serve as a cornerstone for the rise of Industry 5.0. However, current systems are still not effective in providing a high-quality […]
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Optimal placement and sizing of distributed generation for power factor improvement
This study employs the Forward-Backward Sweep (FBS) method in conjunction with the Sea Horse Optimization (SHO) algorithm to optimize the sizing and placement of Distributed Generators (DGs) in a distribution network for the intended case study. Through the integration of MATPOWER toolbox in MATLAB and Torrit software, the network is systematically evaluated under four scenarios […]
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