3069 results — page 1 of 154

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...

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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...

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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...

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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...

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