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作者：Buke, Burak; dos Reis, Goncalo; Platonov, Vadim
作者单位：University of Edinburgh; Universidade Nova de Lisboa; Universidade de Lisboa
摘要：In most service systems, the servers are humans who desire to experience a certain level of idleness. In call centers, this manifests itself as call-avoidance behavior when servers strategically adjust their service rate to strike a balance between the idleness they receive and effort to work harder. Moreover, being human, each server values this tradeoff differently and has different capabilities. We develop a novel framework, relying on measure-valued processes and mean-field game theory, to...
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作者：Cui, Titing; Hamilton, Michael L.
作者单位：University of Tulsa; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
摘要：We study semipersonalized pricing policies in which a seller uses customer features to segment the market and offer segment-specific prices. Although such policies are common, determining the optimal segmentation and corresponding prices is computationally challenging, leading practitioners to rely on heuristic methods that first segment the market and then optimize the prices for each segment. We address this issue by studying the joint optimization of feature-based market segmentation and pr...
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作者：Winschermann, Leoni; Antoniadis, Antonios; Gerards, Marco E. T.; Hoogsteen, Gerwin; Hurink, Johann
作者单位：University of Twente
摘要：Because of the ongoing electrification of transport in combination with limited power grid capacities, efficient ways to schedule the charging of electric vehicles (EVs) are needed for the operation of, for example, large parking lots. Common approaches such as model predictive control repeatedly solve a corresponding offline problem. In this work, we first present and analyze the flow-based offline charging scheduler (FOCS), an offline algorithm to derive an optimal EV charging schedule for a...
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作者：Chen, Zhuoxin; Ma, Will
作者单位：Tsinghua University; Columbia University; Columbia University
摘要：In the newsvendor problem, the goal is to guess the number that will be drawn from some distribution, with asymmetric consequences for guessing too high versus too low. In the data-driven version, the distribution is unknown, and one must work with samples from the distribution. The data-driven newsvendor problem has been studied under many variants: additive versus multiplicative regret, high-probability versus expectation bounds, and different distribution classes. This paper studies all com...
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作者：Arlotto, Alessandro; Keskin, Irem Nur; Wei, Yehua
作者单位：Duke University
摘要：We study a joint inventory placement and online fulfillment model. In the beginning, the inventory is distributed to different warehouses. At each subsequent period, an order arrives from one of the demand regions, and the decision maker makes an irrevocable decision: whether to accept or reject the order and, if accepted, from which warehouse to fulfill it. To study this problem, we introduce the notion of joint (placement and fulfillment) regret, the regret of a given inventory placement and...
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作者：Tian, Feng; Zhang, Feifan; Sun, Peng; Duenyas, Izak
作者单位：University of Hong Kong; Duke University; University of Michigan System; University of Michigan
摘要：We study dynamic contracts that incentivize an agent to exert effort to increase the arrival rate of a Poisson breakthrough, where both the effort cost and the effort level at any time are the agent's private information. Optimally, the principal offers a menu of contracts, each tailored to an agent type (with a different effort cost), specifying an initial payment, a contract deadline, and a payment-upon-arrival process over time. We first fully characterize the optimal contract menu in a two...
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作者：Shafiee, Soroosh; Aolaritei, Liviu; Dorller, Florian; Kuhn, Daniel
作者单位：Cornell University; University of California System; University of California Berkeley; Swiss Federal Institutes of Technology Domain; ETH Zurich; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
摘要：We study optimal transport-based distributionally robust optimization problems in which a fictitious adversary, often envisioned as nature, can choose the distribution of the uncertain problem parameters by reshaping a prescribed reference distribution at a finite transportation cost. In this framework, we show that robustification is intimately related to various forms of variation and Lipschitz regularization even if the transportation cost function fails to be (some power of) a metric. We a...
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作者：Sekar, Shreyas; Siddiq, Auyon
作者单位：University of Toronto; University Toronto Scarborough; University of Toronto; University of California System; University of California Los Angeles
摘要：Two-sided platforms, such as labor marketplaces for hiring freelancers, typically generate revenue by matching prospective buyers and sellers and extracting commissions from completed transactions. Disintermediation, where sellers transact off-platform with buyers to bypass commission fees, can undermine the viability of these marketplaces. Although circumventing the platform allows sellers to avoid commission fees, it also leaves them fully exposed to risky buyers (given the absence of the pl...
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作者：Cheung, Wang Chi; Lyu, Guodong
作者单位：National University of Singapore; Hong Kong University of Science & Technology
摘要：A central issue in (finite horizon) online planning problems is to synthesize the impact of real-time decisions on the subsequent states of the system and the performance in the remaining time horizon (cost-to-go function). A complete resolution often leads to intractable dynamic programming problems. We propose a computationally efficient approach to this problem that attains near-optimal performance in nonstationary environments. More specifically, we study a general class of online planning...
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作者：Wang, Jie; Gao, Rui; Xie, Yao
作者单位：The Chinese University of Hong Kong, Shenzhen; University of Texas System; University of Texas Austin; University System of Georgia; Georgia Institute of Technology
摘要：We study distributionally robust optimization with Sinkhorn distance: a variant of Wasserstein distance based on entropic regularization. We derive a convex programming dual reformulation for general nominal distributions, transport costs, and loss functions. To solve the dual reformulation, we develop a stochastic mirror descent algorithm with biased subgradient estimators and derive its computational complexity guarantees. Finally, we provide numerical examples using synthetic and real data ...
