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作者：Daw, Andrew; Fralix, Brian; Pender, Jamol
作者单位：University of Southern California; Clemson University; Cornell University
摘要：Across domains as diverse as communication channels, computing systems, and public health management, a myriad of real -world queueing systems receive batch arrivals of jobs or customers. In this work, we show that under a natural scaling regime, both the queue -length process and the workload process associated with a properly scaled sequence of infinite -server queueing systems with batch arrivals converge almost surely, uniformly on compact sets, to shot -noise processes. Given the applicab...
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作者：Caldentey, Rene; Hillas, Lisa Aoki; Gupta, Varun
作者单位：University of Chicago; University of Auckland; Northwestern University
摘要：We consider a multiclass, multiserver queueing system, in which customers of different types have heterogeneous preferences over the many servers available. The goal of the service provider is to design a menu of service classes that balances two competing objectives: (1) maximize customers' average matching reward and (2) minimize customers' average waiting time. A service class corresponds to a single queue served by a subset of servers under a first come, first served-assign longest idle se...
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作者：Qu, Zhaonan; Gao, Wenzhi; Hinder, Oliver; Ye, Yinyu; Zhou, Zhengyuan
作者单位：Stanford University; Stanford University; Stanford University; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; New York University
摘要：Preconditioning has long been a staple technique in optimization, often applied to reduce the condition number of a matrix and speed up the convergence of algorithms. Although there are many popular preconditioning techniques in practice, most lack guarantees on reductions in condition number, and the degree to which we can improve over existing heuristic preconditioners remains an important question. In this paper, we study the problem of optimal diagonal preconditioning that achieves maximal...
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作者：Chai, Shiwei; Sun, Xu; Abouee-Mehrizi, Hossein
作者单位：State University System of Florida; University of Florida; University of Miami; University of Waterloo
摘要：Scheduling in the context of many-server queues has received considerable attention. When there are multiple customer classes and many servers, it is common to make simplifying assumptions that result in a low-fidelity model, potentially leading to model misspecification. However, empirical evidence suggests that these assumptions may not accurately reflect real-world scenarios. Although relaxing these assumptions can yield a more accurate high-fidelity model, it often becomes complex and chal...
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作者：Balseiro, Santiago R.; Kroer, Christian; Kumar, Rachitesh
作者单位：Columbia University; Columbia University; Carnegie Mellon University
摘要：Single-leg revenue management is a foundational problem of revenue management that has been particularly impactful in the airline and hotel industry: Given n units of a resource, for example, flight seats, and a stream of sequentially arriving customers segmented by fares, what is the optimal online policy for allocating the resource? Previous work focused on designing algorithms when forecasts are available, which are not robust to inaccuracies in the forecast, or online algorithms with worst...
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作者：W., Martijn; Borm, Peter; Kort, Peter M.
作者单位：Tilburg University
摘要：This article may be used only for the purposes of research, teaching, and/or private study. Commercial use or systematic downloading (by robots or other automatic processes) is prohibited without explicit Publisher approval, unless otherwise noted. For more information, contact permissions@informs.org. The Publisher does not warrant or guarantee the article's accuracy, completeness, merchantability, fitness inclusion of an advertisement in this article, neither constitutes nor implies a guaran...
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作者：Sun, Hailong; Li, Xiaobo; Teo, Chung-Piaw
作者单位：Shanghai Jiao Tong University; National University of Singapore; National University of Singapore; National University of Singapore
摘要：Product bundling is a widely used selling strategy among multiproduct firms, yet designing and pricing bundles optimally remain a complex challenge. This paper addresses this fundamental issue by exploring the selection and pricing of a single bundle from a range of products. For instance, in the single bundle with the rest (SBR) framework, the bundle is optimally chosen and priced, whereas the remaining products are offered individually, collectively maximizing profit. We show that the SBR op...
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作者：Aghaei, Sina; Gomez, Andres; Vayanos, Phebe
作者单位：University of Southern California; University of Southern California
摘要：Decision trees are among the most popular machine learning models and are used routinely in applications ranging from revenue management and medicine to bioinformatics. In this paper, we consider the problem of learning optimal binary classification trees with univariate splits. Literature on the topic has burgeoned in recent years, motivated both by the empirical suboptimality of heuristic approaches and the tremendous improvements in mixed-integer optimization (MIO) technology. Yet, existing...
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作者：Ghuge, Rohan; Gupta, Anupam; Nagarajan, Viswanath
作者单位：University System of Georgia; Georgia Institute of Technology; New York University; University of Michigan System; University of Michigan
摘要：Sequential testing problems involve a complex system with several components, each of which is working with some independent probability. The outcome of each component can be determined by performing a test, which incurs some cost. The overall system status is given by a function f of the outcomes of its components. The goal is to evaluate this function f by performing tests at the minimum expected cost. Although there has been extensive prior work on this topic, provable approximation bounds ...
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作者：Yang, Shuoguang; Li, Xudong; Lan, Guanghui
作者单位：Hong Kong University of Science & Technology; Fudan University; University System of Georgia; Georgia Institute of Technology
摘要：Attention to data-driven optimization approaches, including the well-known stochastic gradient descent method, has grown significantly over recent decades, but data driven constraints have rarely been studied because of the computational challenges of projections onto the feasible set defined by these hard constraints. In this paper, we focus on the nonsmooth convex-concave stochastic minimax regime and formulate the data-driven constraints as expectation constraints. The minimax expectation c...
