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作者：de Ruiter, Frans J. C. T.; Zhen, Jianzhe; den Hertog, Dick
作者单位：Wageningen University & Research; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; Swiss Federal Institutes of Technology Domain; ETH Zurich; University of Amsterdam
摘要：Adjustable robust minimization problems where the objective or constraints depend in a convex way on the adjustable variables are generally difficult to solve. In this paper, we reformulate the original adjustable robust nonlinear problem with a polyhedral uncertainty set into an equivalent adjustable robust linear problem, for which all existing approaches for adjustable robust linear problems can be used. The reformulation is obtained by first dualizing over the adjustable variables and then...
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作者：Goyal, Vineet; Grand-Clement, Julien
作者单位：Columbia University
摘要：Markov decision processes (MDPs) are used to model stochastic systems in many applications. Several efficient algorithms to compute optimal policies have been studied in the literature, including value iteration (VI) and policy iteration. However, these do not scale well, especially when the discount factor for the infinite horizon discounted reward, lambda, gets close to one. In particular, the running time scales as O (1=(1 - lambda)) for these algorithms. In this paper, our goal is to desig...
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作者：Behnezhad, Soheil; Dehghani, Sina; Derakhshan, Mahsa; Hajiaghayi, Mohammedtaghi; Seddighin, Saeed
作者单位：University System of Maryland; University of Maryland College Park
摘要：In the Colonel Blotto game, which was initially introduced by Borel in 1921, two colonels simultaneously distribute their troops across different battlefields. The winner of each battlefield is determined independently by a winner-takes-all rule. The ultimate payoff for each colonel is the number of battlefields won. The Colonel Blotto game is commonly used for analyzing a wide range of applications from the U.S. Presidential election to innovative technology competitions to advertising, sport...
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作者：Gallino, Santiago; Karacaoglu, Nil; Moreno, Antonio
作者单位：University of Pennsylvania; University System of Ohio; Ohio State University; Harvard University
摘要：The impact of delays has been widely studied in various offline services. The focus of this study is online services, andwe explore the impact of in-process delays-measured by website speed-on customer behavior. We leverage novel retail and website speed data to investigate how delays impact online sales and how customer sensitivity to in-process delays varies across the different stages of a customer's shopping journey. We estimate sizable adverse effects of website slowdowns on online sales....
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作者：Wang, Zhongbin; Yang, Luyi; Cui, Shiliang; Ulku, Sezer; Zhou, Yong-Pin
作者单位：Tianjin University; University of California System; University of California Berkeley; Georgetown University; University of Washington; University of Washington Seattle
摘要：In customer-intensive services where service quality increases with service time, service providers commonly pool their agents and give performance bonuses that reward agents for achieving greater customer satisfaction and serving more customers. Conventional wisdom suggests that pooling agents reduce customer wait time while performance bonuses motivate agents to produce high-quality service, both of which should boost customer satisfaction. However, our queueing-game-theoretic analysis revea...
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作者：Rostami, Borzou; Errico, Fausto; Lodi, Andrea
作者单位：Wilfrid Laurier University; Universite de Montreal; Polytechnique Montreal; University of Quebec; Ecole de Technologie Superieure - Canada; Cornell University
摘要：In this paper, we propose a general modeling and solving framework for a large class of binary quadratic programs subject to variable partitioning constraints. Problems in this class have a wide range of applications as many binary quadratic programs with linear constraints can be represented in this form. By exploiting the structure of the partitioning constraints, we propose mixed-integer nonlinear programming (MINLP) and mixedinteger linear programming (MILP) reformulations and show the rel...
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作者：Garg, Jugal; Vegh, Laszlo A.
作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University of London; London School Economics & Political Science
摘要：We present a strongly polynomial algorithm for computing an equilibrium in Arrow-Debreu exchange markets with linear utilities. Our algorithm is based on a variant of the weakly polynomial Duan-Mehlhorn (DM) algorithm. We use the DMalgorithm as a subroutine to identify revealed edges-that is, pairs of agents and goods that must correspond to the best bang-per-buck transactions in every equilibrium solution. Every time a new revealed edge is found, we use another subroutine that decides if ther...
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作者：Nakahira, Yorie; Ferragut, Andres; Wierman, Adam
作者单位：Carnegie Mellon University; University ORT Uruguay; California Institute of Technology
摘要：Many modern schedulers can dynamically adjust their service capacity to match the incoming workload. At the same time, however, unpredictability and instability in service capacity often incur operational and infrastructural costs. In this paper, we seek to characterize optimal distributed algorithms that maximize the predictability, stability, or both when scheduling jobs with deadlines. Specifically, we show that Exact Scheduling minimizes both the stationary mean and variance of the service...
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作者：Hmedi, Hassan; Arapostathis, Ari; Pang, Guodong
作者单位：University of Texas System; University of Texas Austin; Rice University
摘要：We introduce a system-wide safety staffing (SWSS) parameter for multiclass multipool networks of any tree topology, Markovian or non-Markovian, in the Halfin-Whitt regime. This parameter can be regarded as the optimal reallocation of the capacity fluctuations (positive or negative) of order root n when each server pool uses a square-root staffing rule. We provide an explicit formof the SWSS as a function of the systemparameters, which is derived using a graph theoretic approach based on Gaussi...
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作者：Liu, Junyi; Pang, Jong-Shi
作者单位：Tsinghua University; University of Southern California
摘要：This paper proposes the use of a variant of the conditional value-at-risk (CVaR) risk measure, called the interval conditional value-at-risk (In-CVaR), for the treatment of outliers in statistical learning by excluding the risks associated with the left and right tails of the loss. The risk-based robust learning task is to minimize the In-CVaR risk measure of a random functional that is the composite of a piecewise affine loss function with a potentially nonsmooth difference-of-convex statisti...
