Operations Research

最新文章

• Ranking and Contextual Selection AI翻译
  作者：Keslin, Gregory; Nelson, Barry L.; Pagnoncelli, Bernardo; Plumlee, Matthew; Rahimian, Hamed
  作者单位：Northwestern University; Universite Cote d'Azur; SKEMA Business School; Amazon.com; Clemson University
  摘要：This paper proposes a new ranking-and-selection procedure, called ranking and contextual selection, in which covariates provide context for data-driven decisions. Our procedure optimizes over a set of covariate design points off-line and then, given an actual observation of the covariate, makes an online decision based on classification-a distinctly new approach. We prove the existence of an experimental design that yields a pointwise probability of good selection guarantee and derive a postex...
• Distributionally Constrained Black-Box Stochastic Gradient Estimation and Optimization AI翻译
  作者：Lam, Henry; Zhang, Junhui
  作者单位：Columbia University; Columbia University
  摘要：We consider stochastic gradient estimation using only black-box function evaluations, where the function argument lies within a probability simplex. This problem is motivated from gradient-descent optimization procedures in multiple applications in distributionally robust analysis and inverse model calibration involving decision variables that are probability distributions. We are especially interested in obtaining gradient estimators where one or few sample observations or simulation runs app...
• Structural Estimation of Markov Decision Processes in High Dimensional State Space with Finite-Time Guarantees AI翻译
  作者：Zeng, Siliang; Hong, Mingyi; Garcia, Alfredo
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; Texas A&M University System; Texas A&M University College Station
  摘要：We consider the task of estimating a structural model of dynamic decisions by human agent based on the observable history of implemented actions and visited states. This problem has an inherent nested structure: In the inner problem, an optimal policy a given reward function is identified, whereas in the outer problem, a measure of fit is maximized. Several approaches have been proposed to alleviate the computational burden this nested-loop structure, but these methods still suffer from high c...
• 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 ...
• Efficient Algorithms for a Class of Stochastic Hidden Convex Optimization and Its Applications in Network Revenue Management AI翻译
  作者：Chen, Xin; He, Niao; Hu, Yifan; Ye, Zikun
  作者单位：University System of Georgia; Georgia Institute of Technology; Swiss Federal Institutes of Technology Domain; ETH Zurich; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; University of Washington; University of Washington Seattle
  摘要：We study a class of stochastic nonconvex optimization in the form of min(x is an element of X) F(x) := E-xi[f (phi(x, xi))], that is, F is a composition of a convex function f and a random function phi. Leveraging an (implicit) convex reformulation via a variable transformation u = E[phi(x, xi)], we develop stochastic gradient-based algorithms and establish their sample and gradient complexities for achieving an epsilon-global optimal solution. Interestingly, our proposed Mirror Stochastic Gra...
• On (Random-Order) Online Contention Resolution Schemes for the Matching Polytope of (Bipartite) Graphs AI翻译
  作者：MacRury, Calum; Ma, Will; Grammel, Nathaniel
  作者单位：Columbia University; Columbia University; University System of Maryland; University of Maryland College Park
  摘要：Online Contention Resolution Schemes (OCRSs) represent a modern tool for selecting a subset of elements, subject to resource constraints, when the elements are presented to the algorithm sequentially. OCRSs have led to some of the best-known competitive ratio guarantees for online resource allocation problems, with the added benefit of treating different online decisions-accept/reject, probing, pricing-in a unified manner. This paper analyzes OCRSs for resource constraints defined by matchings...
• 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...
• Technical Note: Dynamic Duopolistic Competition with Sticky Prices AI翻译
  作者：Heston, Steven L.; Hu, Bo
  作者单位：University System of Maryland; University of Maryland College Park; George Mason University
  摘要：A paradoxical conclusion arises in a series of game-theoretic models: the limit equilibria retain frictional qualities even as frictions seemingly vanish. This originates in textbook models, such as the differential game by Fershtman and Kamien [Fershtman C, Kamien MI (1987) Dynamic duopolistic competition with sticky prices. Econometrica 55(5):1151-1164] on duopolistic competition with sticky prices. We show that this paradox is an artifact of the type of limit restricted by continuous-time m...
• A Reciprocity Between Tree Ensemble Optimization and Multilinear Optimization AI翻译
  作者：Kim, Jongeun; Richard, Jean-Philippe P.; Tawarmalani, Mohit
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; Purdue University System; Purdue University
  摘要：In this paper, we establish a low-degree polynomially-sized reduction between tree ensemble optimization and optimization of multilinear functions over a Cartesian product of simplices. We use this insight to derive new formulations for tree ensemble optimization problems and to obtain new convex hull results for multilinear polytopes. A computational experiment on multicommodity transportation problems with costs modeled using tree ensembles shows the practical advantage of our formulation re...