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作者：Dupret, Jean-Loup; Hainaut, Donatien
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich; Universite Catholique Louvain
摘要：This paper introduces the generalized policy iteration physics-informed neural network algorithm, a novel numerical scheme for solving continuous-time stochastic optimal control problems in high dimensions when the optimal control does not admit an explicit solution. The proposed iterative deep learning algorithm leverages physicsinformed neural networks on the Hamilton-Jacobi-Bellman residuals in an actor-critic fashion, which is built from the generalized policy iteration technique. It emplo...
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作者：Shen, Tao; Cui, Yifan
作者单位：Zhejiang University; Zhejiang University
摘要：In data-driven demand learning, understanding customer willingness to pay presents a significant challenge because of the complex interplay between various influencing factors. This paper addresses the multifaceted relationship between key demand drivers (e.g., price) and demand outcomes (e.g., sales) and underscores the difficulties in identifying causal effects under endogeneity. To mitigate confounding bias, we introduce proxy variables into the demand learning process. Inspired by the prox...
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作者：Kaps, Christian; Netessine, Serguei
作者单位：Harvard University; University of Pennsylvania
摘要：In this study, we investigate households' investments in behind-the-meter battery storage alongside rooftop solar and examine the effects of these batteries on consumers, the power market, and environmental emissions. We develop a structural estimation model of residential electricity usage that separates observed demand and consumption preferences and lets us estimate a nonfinancial utility that households may have for using self-generated solar power over grid-procured electricity. We call t...
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作者：Lyu, Bochuan; Hicks, Illya, V; Huchette, Joey
作者单位：Rice University; Alphabet Inc.; Google Incorporated
摘要：We study mixed-integer programming formulations for the piecewise linear lower and upper bounds (in other words, piecewise linear relaxations) of nonlinear functions that can be modeled by a new class of combinatorial disjunctive constraints (CDCs), generalized nD-ordered CDCs. We first introduce a general formulation technique to model piecewise linear lower and upper bounds of univariate nonlinear functions concurrently so that it uses fewer binary variables than modeling bounds separately. ...
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作者：Hey, Natascha; Mastromatteo, Iacopo; Muhle-Karbe, Johannes; Webster, Kevin
作者单位：Institut Polytechnique de Paris; Ecole Polytechnique; Imperial College London
摘要：We study statistical arbitrage problems accounting for the nonlinear and transient price impact of metaorders observed empirically. We show that simple explicit trading rules can be derived even for general nonparametric alpha and liquidity signals and also discuss extensions to several impact decay timescales. These results are illustrated using a proprietary data set of Capital Fund Management metaorders, which allows us to calibrate the levels, concavity, and decay parameters of the price i...
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作者：Enikeeva, Farida; Klopp, Olga
作者单位：Universite de Poitiers; Institut Polytechnique de Paris; ENSAE Paris
摘要：Structural changes occur in dynamic networks quite frequently and their detection is an important question in many situations, such as fraud detection or cybersecurity. Real-life networks are often incompletely observed because of individual nonresponse or network size. In the present paper, we consider the problem of change-point detection at a temporal sequence of partially observed networks. The goal is to test whether there is a change in the network parameters. Our approach is based on th...
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作者：Abada, Ibrahim; Ancel, Julien
作者单位：Grenoble Ecole Management; Universite Paris Saclay; Universite PSL; Universite Paris-Dauphine; Ecole Nationale des Ponts et Chaussees; Institut Polytechnique de Paris; Ecole Nationale des Ponts et Chaussees
摘要：In electricity systems, investment in generation capacity is subject to risk. The distribution of uncertain parameters on which investment decisions depend might not be fully observed in historical values. In Europe, this was recently illustrated by the crisis of exceptionally high power prices during the 2021-2023 period, which was subsequently followed by a regime of extremely low and even negative prices. In that vein, although some models of risk aversion modify the distribution of realiza...
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作者：Benade, Gerdus; Procaccia, Ariel D.; Tucker-Foltz, Jamie
作者单位：Boston University; Harvard University; Yale University
摘要：The design of algorithms for political redistricting generally takes one of two approaches: optimize an objective such as compactness or, drawing on fair division, construct a protocol whose outcomes guarantee partisan fairness. We aim to have the best of both worlds by optimizing an objective subject to a binary fairness constraint. As a fairness constraint, we adopt the geometric target, which requires the number of seats won by each party to be at least the average (rounded down) of its out...
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作者：Lidbetter, Thomas; Lin, Kyle Y.
作者单位：Rutgers University New Brunswick; Rutgers University System; Rutgers University Newark; Rutgers University New Brunswick; United States Department of Defense; United States Navy; Naval Postgraduate School
摘要：This paper presents a booby trap game played between a defender and an attacker on a search space, which may be a Lebesque measurable subset of Euclidean space or a network. The defender has several booby traps and chooses where to plant them. The attacker, aware of the presence of these booby traps but not their locations, chooses a subset of the space and collects a reward equal to the Lebesgue measure of the subset. If the attacker does not encounter any booby traps, then the attacker keeps...
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作者：Najafi, Sajjad; Jasin, Stefanus; Uichanco, Joline; Zhao, Jinglong
作者单位：Hautes Etudes Commerciales (HEC) Paris; University of Michigan System; University of Michigan; New York University; New York University Tandon School of Engineering; Boston University
摘要：We study assortment and price optimization under the contextual concavity (CC) model introduced in the literature, which subsumes the well-known multiattribute loss aversion (MLA) model. Unlike context-independent choice models that assume product utilities are unaffected by other alternatives in the assortment, the CC model offers a context-dependent framework that incorporates reference points across multiple attributes and captures prominent context effects (e.g., the compromise effect) wel...
