2025

最新文章

• Budget-Driven Multiperiod Hub Location: A Robust Time-Series Approach AI翻译
  作者：Hu, Jie; Chen, Zhi; Wang, Shuming
  作者单位：Beijing Jiaotong University; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Chinese University of Hong Kong
  摘要：We study the (un)capacitated multiperiod hub location problem with uncertain periodic demands. With a distributionally robust approach that considers time series, we build a model driven by budgets on periodic costs. In particular, we construct a nested ambiguity set that characterizes uncertain periodic demands via a general multivariate time-series model, and to ensure stable periodic costs, we propose to constrain each expected periodic cost within a budget whereas optimizing the robustness...
• On Sinkhorn's Algorithm and Choice Modeling AI翻译
  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 ...
• ORLM: A Customizable Framework in Training Large Models for Automated Optimization Modeling AI翻译
  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...
• Crosscutting Areas On Consistency of Signature Using Lasso AI翻译
  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...
• Random Graph Matching at Otter's Threshold via Counting Chandeliers AI翻译
  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...
• Maximum Load Assortment Optimization: Approximation Algorithms and Adaptivity Gaps AI翻译
  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 ...
• Technical Note: On Dynamic Pricing with Covariates AI翻译
  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...
• Stability of a Queue Fed by Scheduled Traffic at Critical Loading AI翻译
  作者：Araman, Victor F.; Glynn, Peter W.
  作者单位：American University of Beirut; Stanford University
  摘要：Consider the workload process for a single server queue with deterministic service times in which customers arrive according to a scheduled traffic process. A scheduled arrival sequence is one in which customers are scheduled to arrive at constant interarrival times, but each customer's actual arrival time is perturbed from her scheduled arrival time by a random perturbation. In this paper, we consider a critically loaded queue in which the service rate equals the arrival rate. Unlike a queue ...
• Search in the Dark: The Case with Recall and Gaussian Learning AI翻译
  作者：Baucells, Manel; Zorc, Sasa
  作者单位：University of Virginia
  摘要：The classic sequential search problem rewards the decision maker with the highest sampled value minus a cost per sample. If the sampling distribution is unknown, then a Bayesian decision maker faces a complex balance between exploration and exploitation. We solve the stopping problem of sampling from a normal distribution with unknown mean and variance and a conjugate prior, a longstanding open problem. The optimal stopping region may be empty (it may be optimal to continue the search regardle...
• Logarithmic Regret in Multisecretary and Online Linear Programs with Continuous Valuations AI翻译
  作者：Bray, Robert L.
  作者单位：Northwestern University
  摘要：I use empirical processes to study how the shadow prices of a linear program that allocates an endowment of nf3 is an element of Rm resources to n customers behave as n -> infinity. I show the shadow prices (i) adhere to a concentration of measure, (ii) converge to a multivariate normal under central-limit-theorem scaling, and (iii) have a variance that decreases like Theta(1/n). I use these results to prove that the expected regret in an online linear program is Theta(log n), both when the cu...