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31 Papers in 2024

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Load-flow analyses of islanded microgrids commonly assumes constant line admittances with respect to the grid's nominal frequency. This article analyzes erro...

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The arithmetic-geometric index is a newly proposed degree-based graph invariant in mathematical chemistry. We give a sharp upper bound on the value of this ...

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Transit authorities are rapidly replacing conventional buses with electric ones because of the increasing concerns about air quality, greenhouse gas emission...

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Millions of oil and gas wells are abandoned and orphaned around the world. Due to funding shortfalls, many abandoned and orphaned wells remain unplugged and ...

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Augmented Lagrangian (AL) methods are a well known class of algorithms for solving constrained optimization problems. They have been extended to the solution...

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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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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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Efficiently solving a vehicle routing problem (\(\mathcal{VRP}\)) in a practical runtime is a critical challenge for delivery management companies. This pa...

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This paper describes a planning problem faced by a fast-growing petroleum company in West Africa. The problem is a complex variant of the petrol station repl...

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Cellular solids are structures which have applications in mechanical engineering to make lightweight structures and heat exchangers, in biomedical engineer...

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Vehicle routing problems (VRPs) with deadlines have received significant attention around the world. Motivated by a real-world food delivery problem, we assu...

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We reassess Boehmer et al. (2021, BJZZ)'s seminal work on the predictive power of retail order imbalance (ROI) for future stock returns. First, we replicate ...

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We develop a trust-region method for minimizing the sum of a smooth term \(f\) and a nonsmooth term \(h\), both of which can be nonconvex. Each iteratio...

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The purpose of the present note is to bring clarifications to certain concepts and surrounding notation of Aravkin et al. (2022). All results therein contin...

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We develop a worst-case evaluation complexity bound for trust-region methods in the presence of unbounded Hessian approximations. We use the algorithm of Ar...

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We develop an interior-point method for nonsmooth regularized bound-constrained optimization problems. Our method consists of iteratively solving a sequence...

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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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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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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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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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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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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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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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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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Determining optimal inventory replenishment decisions requires balancing the costs of excess inventory with shortage risks. While demand uncertainty has been...

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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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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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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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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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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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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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