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作者：Thomae, Simon; Schiffer, Maximilian; Wiesemann, Wolfram
作者单位：RWTH Aachen University; Technical University of Munich; Technical University of Munich; Imperial College London
摘要：Multistage decision making under uncertainty, where decisions are taken under sequentially revealing uncertain problem parameters, is often essential to faithfully model managerial problems. Given the significant computational challenges involved, these problems are typically solved approximately. This short note introduces an algorithmic framework that revisits a popular approximation scheme for multistage stochastic programs and improves on it to deliver superior policies in the stochastic s...
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作者：Qu, Zhaonan; Galichon, Alfred; Gao, Wenzhi; Ugander, Johan
作者单位：New Jersey Institute of Technology; Columbia University; New York University; New York University; Institut d'Etudes Politiques Paris (Sciences Po); Stanford University; Stanford University
摘要：For a broad class of models widely used in practice for choice and ranking data based on the Luce choice axiom, including the Bradley-Terry-Luce and Plackett-Luce models, we show that the associated maximum likelihood estimation problems are equivalent to a classic matrix-balancing problem with target row and column sums. This perspective opens doors between two seemingly unrelated research areas and allows us to unify existing algorithms in the choice-modeling literature as special instances ...
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作者：Gorissen, Bram L.; den Hertog, Dick; Reusken, Meike
作者单位：Harvard University; Harvard University Medical Affiliates; Massachusetts General Hospital; Harvard University; Harvard Medical School; Harvard University; Massachusetts Institute of Technology (MIT); Broad Institute; University of Amsterdam; Tilburg University; Wageningen University & Research
摘要：In this paper we identify a new class of nonconvex optimization problems that can be equivalently reformulated to convex ones. These nonconvex problems can be characterized by convex functions with bilinear arguments. We describe several examples of important applications that have this structure. These include the problems with variable coefficients, the dual of robust nonlinear optimization problems that are convex in the optimization variables and concave in the uncertain parameters, and in...
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作者：Huang, Chenyu; Tang, Zhengyang; Hu, Shixi; Jiang, Ruoqing; Zheng, Xin; Ge, Dongdong; Wang, Benyou; Wang, Zizhuo
作者单位：Shanghai University of Finance & Economics; The Chinese University of Hong Kong, Shenzhen; The Chinese University of Hong Kong, Shenzhen; Shenzhen Research Institute of Big Data; Columbia University; Tsinghua University; Duke University; Shanghai Jiao Tong University; The Chinese University of Hong Kong, Shenzhen
摘要：Optimization modeling plays a critical role in the application of Operations Research (OR) tools to address real-world problems, yet they pose challenges and require extensive expertise from OR experts. With the advent of large language models (LLMs), new opportunities have emerged to streamline and automate such tasks. However, current research predominantly relies on closed-source LLMs, such as GPT-4, along with extensive prompt engineering techniques. This reliance stems from the scarcity o...
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作者：Guo, Xin; Wang, Binnan; Zhang, Ruixun; Zhao, Chaoyi
作者单位：University of California System; University of California Berkeley; Peking University; Peking University; Peking University; Peking University; Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT)
摘要：Signatures are iterated path integrals of continuous and discrete-time processes, and their universal nonlinearity linearizes the problem of feature selection in time series data analysis. This paper studies the consistency of signature using Lasso regression, both theoretically and numerically. We establish conditions under which the Lasso regression is consistent both asymptotically and in finite sample. Furthermore, we show that the Lasso regression is more consistent with the Ito signature...
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作者：Mao, Cheng; Wu, Yihong; Xu, Jiaming; Yu, Sophie H.
作者单位：University System of Georgia; Georgia Institute of Technology; Yale University; Duke University; University of Pennsylvania
摘要：We propose an efficient algorithm for graph matching based on similarity scores constructed from counting a certain family of weighted trees rooted at each vertex. For two Erdos-Renyi graphs G(n,q) whose edges are correlated through a latent vertex correspondence, we show that this algorithm correctly matches all but a vanishing fraction of the vertices with high probability, provided that nq -> infinity and the edge correlation coefficient rho satisfies rho(2) > alpha approximate to 0:338, wh...
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作者：El Housni, Omar; Ibn Brahim, Marouane; Segev, Danny
作者单位：Cornell University; Tel Aviv University; Tel Aviv University
摘要：Motivated by modern-day applications such as attended home delivery and preference-based group scheduling, where decision makers wish to steer a large number of customers toward choosing the exact same alternative, we introduce a novel class of assortment optimization problems, referred to as maximum load assortment optimization. In such settings, given a universe of substitutable products, we are facing a stream of customers, each choosing between either selecting a product out of an offered ...
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作者：Wang, Hanzhao; Talluri, Kalyan; Li, Xiaocheng
作者单位：Imperial College London
摘要：We consider dynamic pricing with covariates under a generalized linear demand model: A seller can dynamically adjust the price of a product over a horizon of T time periods, and at each time period t, the demand of the product is jointly determined by the price and an observable covariate vector xt is an element of Rd through a generalized linear model with unknown coefficients. Most of the existing literature assumes the covariate vectors xts are independently and identically distributed (i.i...
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作者：Charlet, Nils; Van Houdt, Benny
作者单位：University of Antwerp
摘要：Recently it was shown that the response time of first-come-first-served (FCFS) scheduling can be stochastically and asymptotically improved upon by the Nudge scheduling algorithm in case of light-tailed job size distributions. Such improvements are feasible even when the jobs are partitioned into two types, and the scheduler only has information about the type of incoming jobs (but not their size). In this paper, we introduce Nudge*(M) scheduling, where basically any incoming type 1 job is all...
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作者：Li, Zihao; Wang, Hao; Yan, Zhenzhen
作者单位：National University of Singapore; Chinese Academy of Sciences; University of Science & Technology of China, CAS; Nanyang Technological University; Nanyang Technological University
摘要：We study a fully online matching problem with general stochastic arrivals and departures. In this model, each online arrival follows a known identical and independent distribution over a fixed set of agent types. Its sojourn time is unknown in advance and follows type-specific distributions with known expectations. The goal is to maximize the weighted reward from successful matches. To solve this problem, we propose a linear program (LP)-based algorithm whose competitive ratio is lower bounded...
