2025

最新文章

• Jointly Modeling and Clustering Tensors in High Dimensions AI翻译
  作者：Cai, Biao; Zhang, Jingfei; Sun, Will Wei
  作者单位：City University of Hong Kong; Emory University; Purdue University System; Purdue University
  摘要：We consider the problem of jointly modeling and clustering populations of tensors by introducing a high-dimensional tensor mixture model with heterogeneous covariances. To effectively tackle the high dimensionality of tensor objects, we employ plausible dimension reduction assumptions that exploit the intrinsic structures of tensors, such as low rankness in the mean and separability in the covariance. In estimation, we develop an efficient high-dimensional expectation conditional maximization ...
• Application-Driven Learning: A Closed-Loop Prediction and Optimization Approach Applied to Dynamic Reserves and Demand Forecasting AI翻译
  作者：Dias, Joaquim; Street, Alexandre; Homem-de-Mello, Tito; Munoz, Francisco D.
  作者单位：Universidad Adolfo Ibanez
  摘要：Decision making is generally modeled as sequential forecast-decision steps with no feedback, following an open-loop approach. For instance, in the electricity sector, system operators use the forecast-decision approach followed by ad hoc rules to determine reserve requirements and biased net load forecasts to guard the system against renewable generation and demand uncertainty. Such procedures lack technical formalism to minimize operating and reliability costs. We present a new closed-loop fr...
• Data-Driven Clustering and Feature-Based Retail Electricity Pricing with Smart Meters AI翻译
  作者：Keskin, N. Bora; Li, Yuexing; Sunar, Nur
  作者单位：Duke University; Johns Hopkins University; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine
  摘要：We consider an electric utility company that serves retail electricity customers over a discrete-time horizon. In each period, the company observes the customers' consumption and high-dimensional features on customer characteristics and exogenous factors. A distinctive element of our work is that these features exhibit three types of heterogeneity-over time, customers, or both. Based on the consumption and feature observations, the company can dynamically adjust the retail electricity price at...
• Assigning and Scheduling Generalized Malleable Jobs Under Subadditive or Submodular Processing Speeds AI翻译
  作者：Fotakis, Dimitris; Matuschke, Jannik; Papadigenopoulos, Orestis
  作者单位：National Technical University of Athens; KU Leuven; Columbia University
  摘要：Malleable scheduling is a model that captures the possibility of parallelization to expedite the completion of time-critical tasks. A malleable job can be allocated and processed simultaneously on multiple machines, occupying the same time interval on all these machines. We study a general version of this setting, in which the functions determining the joint processing speed of machines for a given job follow different discrete concavity assumptions (subadditivity, fractional subadditivity, su...
• Stochastic Optimization Approaches for an Operating Room and Anesthesiologist Scheduling Problem AI翻译
  作者：Tsang, Man Yiu; Shehadeh, Karmel S.; Curtis, Frank E.; Hochman, Beth R.; Brentjens, Tricia E.
  作者单位：Lehigh University; NewYork-Presbyterian Hospital; Columbia University; Columbia University; NewYork-Presbyterian Hospital
  摘要：We propose combined allocation, assignment, sequencing, and scheduling problems under uncertainty involving multiple operation rooms (ORs), anesthesiologists, and surgeries as well as methodologies for solving such problems. Specifically, given sets of ORs, regular anesthesiologists, on -call anesthesiologists, and surgeries, our methodologies solve the following decision -making problems simultaneously: (1) an allocation problem that decides which ORs to open and which on -call anesthesiologi...
• Generalization Guarantees for Multi-Item Profit Maximization: Pricing, Auctions, and Randomized Mechanisms AI翻译
  作者：Balcan, Maria-Florina; Sandholm, Tuomas; Vitercik, Ellen
  作者单位：Carnegie Mellon University; Stanford University; Stanford University
  摘要：We study multi-item profit maximization when there is an underlying distribution over buyers' values. In practice, a full description of the distribution is typically unavailable, so we study the setting where the mechanism designer only has samples from the distribution. If the designer uses the samples to optimize over a complex mechanism class- such as the set of all multi-item, multibuyer mechanisms-a mechanism may have high average profit over the samples, but low expected profit. This ra...
• Optimal Routing Under Demand Surges: The Value of Future Arrival Rates AI翻译
  作者：Chen, Jinsheng; Dong, Jing; Shi, Pengyi
  作者单位：Agency for Science Technology & Research (A*STAR); A*STAR - Singapore Institute of Manufacturing Technology (SIMTech); Columbia University; Purdue University System; Purdue University
  摘要：Motivated by the growing availability of advanced demand forecast tools, we study how to use future demand information in designing routing strategies in queueing sys-tems under demand surges. We consider a parallel server system operating in a nonstation-ary environment with general time-varying arrival rates. Servers are cross-trained to help nonprimary customer classes during demand surges. However, such flexibility comes with various operational costs, such as a loss of efficiency and inco...
• Episodic Bayesian Optimal Control with Unknown Randomness Distributions AI翻译
  作者：Shapiro, Alexander; Zhou, Enlu; Lin, Yifan; Wang, Yuhao
  作者单位：University System of Georgia; Georgia Institute of Technology
  摘要：Stochastic optimal control with unknown randomness distributions has been studied for a long time, encompassing robust control, distributionally robust control, and adaptive control. We propose a new episodic Bayesian approach that incorporates Bayesian learning with optimal control. In each episode, the approach learns the randomness distribution with a Bayesian posterior and subsequently solves the corresponding Bayesian average estimate of the true problem. The resulting policy is exercised...
• Binary Diversification Characterizes Exact Capacities AI翻译
  作者：Hartmann, Lorenz; Kauffeldt, T. Florian
  作者单位：University of Basel
  摘要：Suggestion for abstract without references: In this paper, we present the first axiomatic characterization of preferences that can be represented by a Choquet integral with respect to an exact capacity. The characterizing axiom, binary diversification, is novel and reflects an inclination for bets on events, thereby capturing a specific type of ambiguity aversion. Furthermore, we demonstrate that the three capacity classes balanced, exact, and convex fully exhaust all levels of our family of k...
• Monetizing Positive Externalities to Mitigate the Infrastructure Underinvestment Problem AI翻译
  作者：Bai, Hao; Bensoussan, Alain; Briest, Gordon; Chevalier-Roignant, Benoi
  作者单位：University of Manchester; University of Texas System; University of Texas Dallas; Otto von Guericke University; emlyon business school
  摘要：Many cities face challenges in financing their infrastructure. If a decision maker cannot capture all the benefits of its investment, there is a risk of underinvestment. Hong Kong's transit operator designed a scheme in which it not only receives fare revenues, but also participates in a property management business, exploiting the positive externalities of public transport on nearby property prices. We develop a stochastic Stackelberg game of timing to explore the rationale of this scheme. Th...