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We use stochastic dynamic programming to design and solve an extended structural setting for which the illiquidity of the firm's assets under liquidation i...

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In this study, we investigate the best remanufacturing strategy for the original equipment manufacturer (OEM) and independent remanufacturer (IR) in an innov...

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Position estimation in Multi-Robot Systems (MRS) relies on relative angle or distance measurements between the robots, which generally deteriorate as dista...

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Les systèmes de production d'énergie renouvelables hybrides (SPERH), où l'on peut trouver deux ou plusieurs moyens de production d'énergie renouvelables co-l...

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We study how the financial literature has evolved in scale, research team composition, and article topicality across 32 finance-focused academic journals fro...

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Nous considérons la méthode de surrelaxation successive généralisée (GSOR) pour la résolution d’une classe de systèmes de points de selle à trois par trois...

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Personnel scheduling consists in determining employee work schedules (sequences of work shifts and days off) to cover the demands of multiple jobs over a pl...

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The multi-depot scheduling problem (MDVSP) is one of the most studied problem in public transport service planning. It consists of assigning buses to each ti...

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Crew pairing problems (CPP) are regularly solved by airlines to produce crew schedules. The goal of CPPs is to find a set of pairings (sequence of flights a...

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We explore the realized alpha-performance heterogeneity in green and brown stocks' universes using the peer performance ratios of Ardia and Boudt(2018). Focu...

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The conjugate gradient (CG) method is a classic Krylov subspace method for solving symmetric positive definite linear systems. We introduce an analogous sem...

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We consider the problem of training a deep neural network with nonsmooth regularization to retrieve a sparse and efficient sub-structure. Our regularizer is ...

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We study an integrated multi-product production and distribution problem considering a network of multiple plants and customers, who are geographically dispe...

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Statistical learning models are proposed for the prediction of the probability of a spike in the electricity DART (day-ahead minus real-time price) spread. A...

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The transmission of the contagious Coronavirus disease (COVID-19) is highly dependent on individual viral dynamics. Reverse-transcription quantitative polyme...

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We formulate an efficient approximation for multi-agent batch reinforcement learning, the approximated multi-agent fitted Q iteration (AMAFQI). We present a ...

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This paper considers the pricing of a new product in the face of sophisticated consumer behaviors. At the individual level, consumers are forward-looking, wh...

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Nous proposons dans cet article un algorithme rapide pour calculer une borne supérieure au problème de la gestion de la puissance des utilisateurs d'un e...

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A new factor-based representation of implied volatility surfaces is proposed. The factors adequately capture the moneyness and maturity slopes, the smile att...

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Une livraison plus rapide, des frais d'expédition réduits et une plus grande probabilité de disponibilité des produits sont certains des avantages offerts pa...

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