Operations Research

最新文章

• Long-Term Partnership for Achieving Efficient Capacity Allocation AI翻译
  作者：Liu, Fang; Lewis, Tracy R.; Song, Jing-Sheng; Kuribko, Nataliya
  作者单位：Nanyang Technological University; Duke University
  摘要：We consider a capacity provider and a group of independent buyers who partner to share a scarce but expensive-to-build capacity over a finite horizon under privately informed demand conditions. At the beginning of the time horizon, the capacity provider must invest in building capacity; all members may invest in increasing their own and possibly other members' market sizes. Then each member observes and updates its private, history-dependent demand information over time. Because the value of t...
• Data-Driven Incentive Design in the Medicare Shared Savings Program AI翻译
  作者：Aswani, Anil; Shen, Zuo-Jun Max; Siddiq, Auyon
  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; University of California System; University of California Los Angeles
  摘要：The Medicare Shared Savings Program (MSSP) was created under the Patient Protection and Affordable Care Act to control escalating Medicare spending by incentivizing providers to deliver healthcare more efficiently. Medicare providers that enroll in the MSSP earn bonus payments for reducing spending to below a risk-adjusted financial benchmark that depends on the provider's historical spending. To generate savings, a provider must invest to improve efficiency, which is a cost that is absorbed e...
• Coordinating Pricing and Inventory Replenishment with Nonparametric Demand Learning AI翻译
  作者：Chen, Boxiao; Chao, Xiuli; Ahn, Hyun-Soo
  作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
  摘要：We consider a firm (e.g., retailer) selling a single nonperishable product over a finite-period planning horizon. Demand in each period is stochastic and price sensitive, and unsatisfied demands are backlogged. At the beginning of each period, the firm determines its selling price and inventory replenishment quantity with the objective of maximizing total profit, but it knows neither the average demand (as a function of price) nor the distribution of demand uncertainty a priori; hence, it has ...
• Dynamic Selling Mechanisms for Product Differentiation and Learning AI翻译
  作者：Keskin, N. Bora; Birge, John R.
  作者单位：Duke University; University of Chicago
  摘要：We consider a firm that designs a vertically differentiated product line for a population of customers with heterogeneous quality sensitivities. The firm faces an uncertainty about the cost of quality, and we formulate this uncertainty as a belief distribution on a set of cost models. Over a time horizon of T periods, the firm can dynamically adjust its menu and make noisy observations on the underlying cost model through customers' purchasing decisions. We characterize how optimal product dif...
• Recovering Best Statistical Guarantees via the Empirical Divergence-Based Distributionally Robust Optimization AI翻译
  作者：Lam, Henry
  作者单位：Columbia University
  摘要：We investigate the use of distributionally robust optimization (DRO) as a tractable tool to recover the asymptotic statistical guarantees provided by the central limit theorem, for maintaining the feasibility of an expected value constraint under ambiguous probability distributions. We show that using empirically defined Burg-entropy divergence balls to construct the DRO can attain such guarantees. These balls, however, are not reasoned from the standard data-driven DRO framework because, by t...
• The Weighted Nonnegative Least-Squares Problem with Implicitly Characterized Points AI翻译
  作者：Fattahi, Ali; Dasu, Sriram; Ahmadi, Reza
  作者单位：University of California System; University of California Los Angeles; University of Southern California
  摘要：The nonnegative least-squares (NNLS) problem is defined as finding the Euclidean distance to a convex cone generated by a set of discrete points in R. In this paper, we study NNLS when the discrete points are implicitly known and there are an exponentially large number of them (e.g., the set of integer feasible solutions of a mixed-integer program). This problem is motivated by a large auto manufacturer that produces mass customized products where the products are configured by choosing a subs...
• Mass Customization and Forecasting Options' Penetration Rates Problem AI翻译
  作者：Fattahi, Ali; Dasu, Sriram; Ahmadi, Reza
  作者单位：University of California System; University of California Los Angeles; University of Southern California
  摘要：Auto manufacturers produce a very large number of feasible configurations that make it impossible to forecast the demand of individual configurations. What the companies do forecast is the penetration rate of each option, which is the percentage of cars that include that option. The current forecasting approach ignores rules for selecting options, and as a result, forecast penetration rates are frequently infeasible, which results in excess inventories, shortages, and customer dissatisfaction....
• Plant Capacity and Attainability: Exploration and Remedies AI翻译
  作者：Kerstens, Kristiaan; Sadeghi, Jafar; Van de Woestyne, Ignace
  作者单位：IESEG School of Management; Centre National de la Recherche Scientifique (CNRS); CNRS - Institute for Humanities & Social Sciences (INSHS); Kharazmi University; KU Leuven
  摘要：The output-oriented plant capacity notion, which has been around for more than two decades, has been empirically applied mainly in the fishery and the hospital sectors. Since its introduction to the literature, a specified problem is that this notion may not be attainable, in that it presupposes potentially unlimited numbers of variable inputs to determine the maximum number of outputs available. However, this lack of attainability has not been explored previously. This paper fills this void b...
• Covariate-Adaptive Optimization in Online Clinical Trials AI翻译
  作者：Bertsimas, Dimitris; Korolko, Nikita; Weinstein, Alexander M.
  作者单位：Massachusetts Institute of Technology (MIT)
  摘要：The decision of how to allocate subjects to treatment groups is of great importance in experimental clinical trials for novel investigational drugs, a multibillion-dollar industry. Statistical power, the ability of an experiment to detect a positive treatment effect when one exists, depends in part on the similarity of the groups in terms of measurable covariates that affect the treatment response. We present a novel algorithm for online allocation that leverages robust mixed-integer optimizat...
• Sequest: A Sequential Procedure for Estimating Quantiles in Steady-State Simulations AI翻译
  作者：Alexopoulos, Christos; Goldsman, David; Mokashi, Anup C.; Tien, Kal-Wen; Wilson, James R.
  作者单位：University System of Georgia; Georgia Institute of Technology; SAS Institute Inc; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; North Carolina State University
  摘要：Sequest is an automated sequential simulation-analysis procedure designed to provide improved point and confidence-interval (CI) estimators for a designated steady-state quantile by the use of batching and sectioning. The procedure incorporates techniques to do the following: (i) reduce the absolute bias of the sectioning-based point estimator caused by atypical simulation initialization or an inadequate sample size, (ii) adjust the batching-based CI half-length to compensate for correlation o...