2022

最新文章

• Market Efficient Portfolios in a Systemic Economy AI翻译
  作者：Awiszus, Kerstin; Capponi, Agostino; Weber, Stefan
  作者单位：Leibniz University Hannover; Columbia University
  摘要：We study the ex ante minimization of market inefficiency, defined in terms of minimum deviation of market prices from fundamental values, from a centralized planner's perspective. Prices are pressured from exogenous trading actions of leveragetargeting banks, which rebalance their portfolios in response to asset shocks. We characterize market inefficiency in terms of two key drivers, the banks' systemic significance and the statistical moments of asset shocks, and develop an explicit expressio...
• Spatio-Temporal Pricing for Ridesharing Platforms AI翻译
  作者：Ma, Hongyao; Fang, Fei; Parkes, David C.
  作者单位：Columbia University; Carnegie Mellon University; Harvard University
  摘要：Ridesharing platforms match drivers and riders to trips, using dynamic prices to balance supply and demand. A challenge is to set prices that are appropriately smooth in space and time, so that drivers with the flexibility to decide how to work will nevertheless choose to accept their dispatched trips rather than drive to another area or wait for higher prices or a better trip. In this work, we propose a complete information model that is simple yet rich enough to incorporate spatial imbalance...
• Naive Learning Through Probability Overmatching AI翻译
  作者：Arieli, Itai; Babichenko, Yakov; Mueller-Frank, Manuel
  作者单位：Technion Israel Institute of Technology; University of Navarra; IESE Business School
  摘要：We analyze boundedly rational updating in a repeated interaction network model with binary actions and binary states. Agents form beliefs according to discretized DeGroot updating and apply a decision rule that assigns a (mixed) action to each belief. We first show that under weak assumptions, random decision rules are sufficient to achieve agreement in finite time in any strongly connected network. Ourmain result establishes that naive learning can be achieved in any large strongly connected ...
• Multiplicative Pacing Equilibria in Auction Markets AI翻译
  作者：Conitzer, Vincent; Kroer, Christian; Sodomka, Eric; Stier-Moses, Nicolas E.
  作者单位：Duke University; Columbia University; Facebook Inc
  摘要：Budgets play a significant role in real-world sequential auction markets such as those implemented by internet companies. To maximize the value provided to auction participants, spending is smoothed across auctions so budgets are used for the best opportunities. Motivated by a mechanism used in practice by several companies, this paper considers a smoothing procedure that relies on pacing multipliers: on behalf of each buyer, the auction market applies a factor between 0 and 1 that uniformly s...
• Crew Assignment with Duty Time Limits for Transport Services: Tight Multicommodity Models AI翻译
  作者：Balakrishnan, Anantaram; Mirchandani, Prakash; Lin, Sifeng
  作者单位：University of Texas System; University of Texas Austin; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; University of Texas System; University of Texas Austin
  摘要：Crew costs account for a significant portion of the operating expenses for transportation service providers, and so utilizing crews effectively is an important priority for these organizations. This paper addresses the core problem of assigning crews to urban transit and other scheduled transportation services at minimum total cost for crew usage, assignment, and transfers, taking into account crew work rules that limit their duty and working times. We propose a new multicommodity flow model w...
• Surgical Case-Mix and Discharge Decisions: Does Within-Hospital Coordination Matter? AI翻译
  作者：Bavafa, Hessam; Ormeci, Lerzan; Savin, Sergei; Virudachalam, Vanitha
  作者单位：University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison; Koc University; University of Pennsylvania; University of Illinois System; University of Illinois Urbana-Champaign
  摘要：We study the problem faced by a profit-maximizing, resource-constrained hospital that controls patient inflows by designing a case-mix of its elective procedures and patient outflows via patient discharges. At the center of our analysis is the model that evaluates hospital profit for any combination of elective portfolio and patient discharge policies. Our model analyzes the impact of patient flow management decisions on the utilization of two main classes of hospital resources: front end (e.g...
• Robust Learning of Consumer Preferences AI翻译
  作者：Feng, Yifan; Caldentey, Rene; Ryan, Christopher Thomas
  作者单位：National University of Singapore; University of Chicago; University of British Columbia
  摘要：This paper studies a class of ranking and selection problems faced by a company that wants to identify the most preferred product out of a finite set of alternatives when consumer preferences are a priori unknown. The only information available is that consumer preferences satisfy two key properties: (i) they are consistent with some unknown true ranking of the alternatives, and (ii) they are strict, namely, no two products are equally preferred. To learn the unknown ranking, the company is ab...
• Iterative Collaborative Filtering for Sparse Matrix Estimation AI翻译
  作者：Borgs, Christian; Chayes, Jennifer T.; Shah, Devavrat; Yu, Christina Lee
  作者单位：University of California System; University of California Berkeley; University of California System; University of California Berkeley; University of California System; University of California Berkeley; Cornell University
  摘要：We consider sparse matrix estimation where the goal is to estimate an n-by-n matrix from noisy observations of a small subset of its entries. We analyze the estimation error of the popularly used collaborative filtering algorithm for the sparse regime. Specifically, we propose a novel iterative variant of the algorithm, adapted to handle the setting of sparse observations. We establish that as long as the number of entries observed at random scale logarithmically larger than linear in n, the e...
• Data-Driven Robust Resource Allocation with Monotonic Cost Functions AI翻译
  作者：Chen, Ye; Markovic, Nikola; Ryzhov, Ilya O.; Schonfeld, Paul
  作者单位：Virginia Commonwealth University; Utah System of Higher Education; University of Utah; University System of Maryland; University of Maryland College Park; University System of Maryland; University of Maryland College Park; University System of Maryland; University of Maryland College Park
  摘要：We consider two-stage planning problems (arising, e.g., in city logistics) in which a resource is first divided among a set of independent regions and then costs are incurred based on the allocation to each region. Costs are assumed to be decreasing in the quantity of the resource, but their precise values are unknown, for example, if they represent difficult expected values. We develop a new data-driven uncertainty model for monotonic cost functions, which can be used in conjunction with robu...
• Stochastic Knapsack Revisited: The Service Level Perspective AI翻译
  作者：Lyu, Guodong; Chou, Mabel C.; Teo, Chung-Piaw; Zheng, Zhichao; Zhong, Yuanguang
  作者单位：National University of Singapore; National University of Singapore; Singapore Management University; South China University of Technology
  摘要：A key challenge in the resource allocation problem is to find near-optimal policies to serve different customers with random demands/revenues, using a fixed pool of capacity (properly configured). In this paper, we study the properties of three classes of allocation policies-responsive (with perfect hindsight), adaptive (with information updates), and anticipative (with forecast information) policies. These policies differ in how the information on actual demand and revenue of each customer is...