6期

最新文章

• Asymptotic Optimality of Semi-Open-Loop Policies in Markov Decision Processes with Large Lead Times AI翻译
  作者：Bai, Xingyu; Chen, Xin; Li, Menglong; Stolyar, Alexander
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University System of Georgia; Georgia Institute of Technology; City University of Hong Kong; University of Illinois System; University of Illinois Urbana-Champaign
  摘要：We consider a generic Markov decision process (MDP) with two controls: one control taking effect immediately and the other control whose effect is delayed by a positive lead time. As the lead time grows, one naturally expects that the effect of the delayed action only weakly depends on the current state, and decoupling the delayed action from the current state could provide good controls. The purpose of this paper is to substantiate this decoupling intuition by establishing asymptotic optimali...
• Optimal Subscription Planning for Digital Goods AI翻译
  作者：Alaei, Saeed; Makhdoumi, Ali; Malekian, Azarakhsh
  作者单位：Alphabet Inc.; Google Incorporated; Duke University; University of Toronto
  摘要：We consider a media service provider that gives users access to digital goods through subscription. In our model, different types of users with heterogeneous usage rates repeatedly use a platform over a period of time. There are multiple item types on the platform, and the value of an item to a user is random and depends on both the user type and the item type. The design of the platform's subscription planning comprises selecting a subscription fee for each set of item types. Before the begin...
• Optimizing Risk-Balancing Return Under Discrete Choice Models AI翻译
  作者：Li, Hongmin; Webster, Scott
  作者单位：Arizona State University; Arizona State University-Tempe
  摘要：We examine a firm's pricing decision when managing a broad product line with the goal of optimally balancing the expected return on product investment with the revenue or profit risk associated with uncertain customer choices. We consider the multinomial logit (MNL) model and the mean-variance objective function and illustrate how the level of risk tolerance influences the firm's optimal markups. We show that the solution approach and results generalize to the nested logit (NL) choice model an...
• A Decomposition Algorithm with Fast Identification of Critical Contingencies for Large-Scale Security-Constrained AC-OPF AI翻译
  作者：Curtis, Frank E.; Molzahn, Daniel K.; Tu, Shenyinying; Wachter, Andreas; Wei, Ermin; Wonge, Elizabeth
  作者单位：Lehigh University; University System of Georgia; Georgia Institute of Technology; Northwestern University; Northwestern University; University of California System; University of California San Diego
  摘要：A decomposition algorithm for solving large-scale security-constrained AC optimal power flow problems is presented. The formulation considered is the one used in the Advanced Research Projects Agency-Energy Grid Optimization Competition, Challenge 1, held from November 2018 through October 2019. Algorithmic strategies are proposed for contingency selection, fast contingency evaluation, handling complementarity constraints, avoiding issues related to degeneracy, and exploiting parallelism. The ...
• Customized Dynamic Pricing When Customers Develop a Habit or Satiation AI翻译
  作者：Chen, Wen; He, Ying; Bansal, Saurabh
  作者单位：Providence College; University of Southern Denmark; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
  摘要：We study a dynamic pricing problem in which a firm chooses prices over multiple periods when consumers are state dependent; that is, they develop a habit or satiation from their past consumption. We first derive an intertemporal demand function to capture how demand in one period depends on the price in that period and consumption in previous periods through habit or satiation. Subsequently, we formulate the optimal price setting problem for a firm over a multiperiod horizon. We establish that...
• Scheduling Advertising on Cable Television AI翻译
  作者：Souyris, Sebastian; Seshadri, Sridhar; Subramanian, Sriram
  作者单位：Rensselaer Polytechnic Institute; University of Illinois System; University of Illinois Urbana-Champaign
  摘要：Advertisement scheduling is a daily essential operational process in the television business. Efficient distribution of viewers among advertisers allows the television network to satisfy contracts and increase ad sale revenues. Ad scheduling is a challenging multiperiod, mixed-integer programming problem in which the network must create schedules to meet advertisers' campaign goals and maximize ad revenues. Each campaign must meet a specific target group of viewers and a unique set of constrai...
• Revenue Management with Heterogeneous Resources: Unit Resource Capacities, Advance Bookings, and Itineraries over Time Intervals AI翻译
  作者：Rusmevichientong, Paat; Sumida, Mika; Topaloglu, Huseyin; Bai, Yicheng
  作者单位：University of Southern California
  摘要：We study revenue management problems with heterogeneous resources, each with unit capacity. An arriving customer makes a booking request for a particular interval of days in the future. We offer an assortment of resources in response to each booking request. The customer makes a choice within the assortment to use the chosen resource for her desired interval of days. The goal is to find a policy that determines an assortment of resources to offer to each customer to maximize the total expected...
• From Proper Scoring Rules to Max-Min Optimal Forecast Aggregation AI翻译
  作者：Neyman, Eric; Roughgarden, Tim
  作者单位：Columbia University
  摘要：This paper forges a strong connection between two seemingly unrelated forecasting problems: incentive-compatible forecast elicitation and forecast aggregation. Proper scoring rules are the well-known solution to the former problem. To each such rule s, we associate a corresponding method of aggregation, mapping expert forecasts and expert weights to a consensus forecast, which we call quasi-arithmetic (QA) pooling with respect to s. We justify this correspondence in several ways: QA pooling wi...
• Pricing Under Uncertainty in Multi-Interval Real-Time Markets AI翻译
  作者：Cho, Jehum; Papavasiliou, Anthony
  摘要：Recent research has demonstrated that real-time auctions can generate the need for side payments, even if the market clearing models are convex, because of the rolling nature of real-time market clearing. This observation has inspired proposals for modifying the real-time market-clearing model in order to account for binding past decisions. We extend this analysis in order to account for uncertainty by proposing a real-time market clearing model with look-ahead and an endogenous representation...
• Enhanced Balancing of Bias-Variance Tradeoff in Stochastic Estimation: A Minimax Perspective AI翻译
  作者：Lam, Henry; Zhang, Xinyu; Zhang, Xuhui
  作者单位：Columbia University; Stanford University
  摘要：Biased stochastic estimators, such as finite differences for noisy gradient estimation, often contain parameters that need to be properly chosen to balance impacts from the bias and the variance. Although the optimal order of these parameters in terms of the simulation budget can be readily established, the precise best values depend on model characteristics that are typically unknown in advance. We introduce a framework to construct new classes of estimators based on judicious combinations of...