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作者：Jiang, Ruiwei; Guan, Yongpei
作者单位：University of Michigan System; University of Michigan; State University System of Florida; University of Florida
摘要：In this paper, we develop a risk-averse two-stage stochastic program (RTSP) that explicitly incorporates the distributional ambiguity covering both discrete and continuous distributions. We formulate RTSP from the perspective of distributional robustness by hedging against the worst-case distribution within an ambiguity set and considering the corresponding expected total cost. In particular, we derive an equivalent reformulation for RTSP that indicates that each worst-case expectation over an...
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作者：Zhou, Junjie; Chen, Ying-Ju
作者单位：National University of Singapore; Hong Kong University of Science & Technology; Hong Kong University of Science & Technology
摘要：In this paper, we consider a model with a monopoly firm who sells social goods sequentially to a group of customers in a network. We show that, with symmetric social interactions, the optimal pricing under arbitrary launch sequence is independent of customers' network positions, the launch sequence, and the underlying social interaction relations among customers. This generalizes the previous network-independent prices in the simultaneous-launch case. Therefore, for any given sequence, the fir...
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作者：Jagabathula, Srikanth; Subramanian, Lakshminarayanan; Venkataraman, Ashwin
作者单位：New York University; New York University
摘要：We consider the problem of segmenting a large population of customers into nonoverlapping groups with similar preferences, using diverse preference observations such as purchases, ratings, clicks, and so forth, over subsets of items. We focus on the setting where the universe of items is large (ranging from thousands to millions) and unstructured (lacking well-defined attributes) and each customer provides observations for only a few items. These data characteristics limit the applicability of...
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作者：Liu, Lindong; Qi, Xiangtong; Xu, Zhou
作者单位：Chinese Academy of Sciences; University of Science & Technology of China, CAS; Hong Kong University of Science & Technology; Hong Kong Polytechnic University
摘要：In this paper we propose a new instrument, a simultaneous penalization and subsidization, for stabilizing the grand coalition and enabling cooperation among all players of an unbalanced cooperative game. The basic idea is to charge a penalty z from players who leave the grand coalition, and at the same time provide a subsidy omega to players who stay in the grand coalition. To formalize this idea, we establish a penalty-subsidy function omega(z) based on a linear programming model, which allow...
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作者：Ryzhov, Ilya O.
作者单位：University System of Maryland; University of Maryland College Park; University System of Maryland; University of Maryland College Park
摘要：We propose a framework for targeting and selection (T&S), a new problem class in simulation optimization where the objective is to select a simulation alternative whose mean performance matches a prespecified target as closely as possible. T&S resembles the more well-known problem of ranking and selection but presents unexpected challenges: for example, a one-step look-ahead method may produce statistically inconsistent estimates of the values, even under very standard normality assumptions. W...
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作者：Fazel-Zarandi, Mohammad M.; Kaplan, Edward H.
作者单位：Yale University; Massachusetts Institute of Technology (MIT); Yale University; Yale University
摘要：The first-come, first-served (FCFS) stochastic matching model, where each server in an infinite sequence is matched to the first eligible customer from a second infinite sequence, developed from queueing problems addressed by Kaplan (1984) in the context of public housing assignments. The goal of this model is to determine the matching rates between eligible customer types and server types, that is, the fraction of all matches that occur between type-i customers and type- j servers. This model...
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作者：Emadi, Seyed Morteza; Swaminathan, Jayashankar M.
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine
摘要：Designing modern call centers requires an understanding of callers' patience and abandonment behavior. Using a Cox regression analysis, we show that callers' abandonment behavior may differ based on their contact history, and changes across their different contacts. We control for caller heterogeneity using a two-step grouped-fixed effect method. This analysis shows that differences in callers' abandonment behavior are not only driven by their heterogeneity but also by differences in their bel...
