Operations Research

最新文章

• To Batch or Not to Batch? Impact of Admission Batching on Emergency Department Boarding Time and Physician Productivity AI翻译
  作者：Feizi, Arshya; Carson, Anita; Jaeker, Jillian Berry; Baker, William Evan
  作者单位：Harvard University; Boston University; University of Vermont; University of Vermont Medical Center
  摘要：We study the behavior of batching by discretionary workers in the first stage of a two-stage queuing system and explore the trade-off it causes between their productivity and second stage wait times. Specifically, we focus on the behavior of batching admissions by emergency department (ED) physicians. Using data from a large hospital, we show that the probability of batching admissions is increasing in the hour of an ED physician's shift, and that batched patients experience a 4.7% longer dela...
• Sequential Mechanisms with Ex Post Individual Rationality AI翻译
  作者：Ashlagi, Itai; Daskalakis, Constantinos; Haghpanah, Nima
  作者单位：Stanford University; Massachusetts Institute of Technology (MIT); Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
  摘要：We study optimal mechanisms for selling multiple products to a buyer who learns her values for those products sequentially. A mechanism may use static prices or adjust them over time, and it may sell the products separately or as bundles. We study mechanisms that provide the buyer a nonnegative ex post utility. We show that there exists an optimal mechanism that determines the allocation of each product as soon as the buyer learns her value for that product. This observation allows us to solve...
• Information Retrieval Under Network Uncertainty: Robust Internet Ranking AI翻译
  作者：Timonina-Farkas, Anna; Seifert, Ralf W.
  作者单位：Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; International Institute for Management Development (IMD)
  摘要：Internet ranking algorithms play a crucial role in information technologies and numerical analysis due to their efficiency in high dimensions and wide range of possible applications, including scientometrics and systemic risk in finance (SinkRank, DebtRank, etc.). The traditional approach to internet ranking goes back to the seminal work of Sergey Brin and Larry Page, who developed the initial method PageRank (PR) in order to rank websites in search engine results. Recent works have studied ro...
• On Finite Adaptability in Two-Stage Distributionally Robust Optimization AI翻译
  作者：Han, Eojin; Bandi, Chaithanya; Nohadani, Omid
  作者单位：Southern Methodist University; National University of Singapore
  摘要：In many real applications, practitioners prefer policies that are interpretable and easy to implement. This tendency is magnified in sequential decision-making settings. In this paper, we leverage the concept of finite adaptability to construct policies for two-stage optimization problems. More specifically, we focus on the general setting of distributional uncertainties affecting the right-hand sides of constraints, because in a broad range of applications, uncertainties do not affect the obj...
• On the Structure of Decision Diagram-Representable Mixed-Integer Programs with Application to Unit Commitment AI翻译
  作者：Salemi, Hosseinali; Davarnia, Danial
  作者单位：Iowa State University
  摘要：Over the past decade, decision diagrams (DDs) have been used to model and solve integer programming and combinatorial optimization problems. Despite successful performance of DDs in solving various discrete optimization problems, their extension to model mixed-integer programs (MIPs), such as those appearing in energy applications, is lacking. More broadly, the question of which problem structures admit a DD representation is still open in the DD community. In this paper, we address this quest...
• Technical Note-The Elliptical Potential Lemma for General Distributions with an Application to Linear Thompson Sampling AI翻译
  作者：Hamidi, Nima; Bayati, Mohsen
  作者单位：Stanford University; Stanford University
  摘要：In this note, we introduce a general version of the well-known elliptical potential lemma that is a widely used technique in the analysis of algorithms in sequential learning and decision-making problems. We consider a stochastic linear bandit setting where decision makers sequentially choose among a set of given actions, observe their noisy rewards, and aim to maximize their cumulative expected reward over a decision-making horizon. The elliptical potential lemma is a key tool for quantifying...
• Finite-Sample Guarantees for Wasserstein Distributionally Robust Optimization: Breaking the Curse of Dimensionality AI翻译
  作者：Gao, Rui
  作者单位：University of Texas System; University of Texas Austin
  摘要：Wasserstein distributionally robust optimization (DRO) aims to find robust and generalizable solutions by hedging against data perturbations in Wasserstein distance. Despite its recent empirical success in operations research and machine learning, existing performance guarantees for generic loss functions are either overly conservative because of the curse of dimensionality or plausible only in large sample asymptotics. In this paper, we develop a nonasymptotic framework for analyzing the out-...
• The Anchor-Robust Project Scheduling Problem AI翻译
  作者：Bendotti, Pascale; Chretienne, Philippe; Fouilhoux, Pierre; Pass-Lanneau, Adele
  作者单位：Electricite de France (EDF); Sorbonne Universite; Centre National de la Recherche Scientifique (CNRS)
  摘要：In project scheduling with uncertain processing times, the decision maker often needs to compute a baseline schedule in advance while guaranteeing that some jobs will not be rescheduled later. Standard robust approaches either produce a schedule with a very large makespan or offer no guarantee on starting times of the jobs. The concept of anchor-robustness is introduced as a middle ground between these approaches. A subset of jobs is said to be anchored if the starting times of its jobs in the...
• A Robust Spectral Clustering Algorithm for Sub-Gaussian Mixture Models with Outliers AI翻译
  作者：Srivastava, Prateek R.; Sarkar, Purnamrita; Hanasusanto, Grani A.
  作者单位：University of Texas System; University of Texas Austin; University of Texas System; University of Texas Austin; University of Texas System; University of Texas Austin
  摘要：We consider the problem of clustering data sets in the presence of arbitrary outliers. Traditional clustering algorithms such as k-means and spectral clustering are known to perform poorly for data sets contaminated with even a small number of outliers. In this paper, we develop a provably robust spectral clustering algorithm that applies a simple rounding scheme to denoise a Gaussian kernel matrix built from the data points and uses vanilla spectral clustering to recover the cluster labels of...
• Managing Queues with Different Resource Requirements AI翻译
  作者：Zychlinski, Noa; Chan, Carri W.; Dong, Jing
  作者单位：Technion Israel Institute of Technology; Columbia University
  摘要：Queueing models that are used to capture various service settings typically assume that customers require a single unit of resource (server) to be processed. However, there are many service settings where such an assumption may fail to capture the heterogeneity in resource requirements of different customers. We propose a multiserver queueing model with multiple customer classes in which customers from different classes may require different amounts of resources to be served. We study the opti...