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This poster conceptually lays out recent advances in trustworthy machine learning (ML) that are of great interest for power systems applications like virtu...
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The truck loading and inventory routing problems are the two most important decisions made by companies replenishing petrol stations. This paper investigates...
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In this work, we study a class of two-player deterministic finite-horizon difference games with coupled inequality constraints, where both players have two t...
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The fine-tuning of Large Language Models (LLMs) has enabled them to recently achieve milestones in natural language processing applications. The emergenc...
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We extend the \(\alpha\)
and \(\beta\)
characteristic functions (CFs) to
cooperative interval games, which constitute an interesting class of games
t...
Bus scheduling in public transit consists in determining a set of bus schedules to cover a set of timetabled trips at minimum cost. This planning process has...
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Yield uncertainty is an important issue in various industries such as agriculture, food, and textile where the production output is reliant on uncontrollable...
BibTeX referenceAlgorithme primal ajoutant des variables pour le problème du partitionnement d'ensemble généralisé
Le problème du partitionnement d'ensemble est un problème de programmation en nombres entiers très étudié. Le problème consiste à trouver une partition de tâ...
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The cosine measure was introduced in 2003 to quantify the richness of a finite positive spanning sets of directions in the context of derivative-free direc...
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Inventory management for slow-moving items is challenging due to their high intermittence and lumpiness. Recent developments in machine learning and computat...
BibTeX referenceThe heterogeneous-fleet electric vehicle routing problem with nonlinear charging functions
This paper introduces the Heterogeneous-Fleet Electric Vehicle Routing Problem with Nonlinear Charging Functions (HEVRP-NL). This problem involves routing a ...
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A challenge in aircraft design optimization is the presence of non-computable, so-called hidden, constraints that do not return a value in certain regions of...
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In this work, we improve the efficiency of Unit Commitment (UC) optimization solvers using a Graph Convolutional Neural Network (GCNN). In power systems, UC ...
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This paper introduces a new step to the Direct Search Method (DSM) to strengthen its convergence analysis. By design, this so-called covering step may e...
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Determining optimal inventory replenishment decisions requires balancing the costs of excess inventory with shortage risks. While demand uncertainty has been...
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In this work, we propose a non-intrusive and training free method to detect behind-the-meter (BTM) electric vehicle (EV) charging events from the data measur...
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The Harwell Subroutine Library (HSL) is a renowned suite of efficient and robust numerical algorithms designed to tackle complex mathematical problems such a...
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We show that the two-stage minimum description length (MDL) criterion widely used to estimate linear change-point (CP) models corresponds to the marginal lik...
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We study the relation between the promotion of a cryptocurrency on Twitter and its return dynamics around pump-and-dump events. By analyzing abnormal retur...
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Monte Carlo (MC) is widely used for the simulation of discrete time Markov chains. We consider the case of a \(d\)
-dimensional continuous state space and w...