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作者：Aouad, Ali; Ji, Jingwei; Shaposhnik, Yaron
作者单位：Massachusetts Institute of Technology (MIT); Stanford University; University of Rochester
摘要：The Pandora's box problem is a core model in economic theory that captures an agent's (Pandora's) search for the best alternative (box). We study an important generalization of the problem in which the agent can either fully open boxes for a certain fee to reveal their exact values or partially open them at a reduced cost. This introduces a new trade-off between information acquisition and cost efficiency. We establish a hardness result and employ an array of techniques in stochastic optimizat...
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作者：Thomae, Simon; Schiffer, Maximilian; Wiesemann, Wolfram
作者单位：RWTH Aachen University; Technical University of Munich; Technical University of Munich; Imperial College London
摘要：Multistage decision making under uncertainty, where decisions are taken under sequentially revealing uncertain problem parameters, is often essential to faithfully model managerial problems. Given the significant computational challenges involved, these problems are typically solved approximately. This short note introduces an algorithmic framework that revisits a popular approximation scheme for multistage stochastic programs and improves on it to deliver superior policies in the stochastic s...
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作者：Deng, Tianhu; Shao, Feiyu; Song, Jing-Sheng Jeannette; Yu, Yi
作者单位：Soochow University - China; Tsinghua University; Duke University; Shanghai University of Finance & Economics
摘要：To enhance supply chain resilience, assembly manufacturers increasingly adopt dual-sourcing strategies, utilizing both regular and faster but costlier express sources for each key component. Although research has focused on single-item systems, coordinating dual-sourced orders across multiple components in an assembly system remains underexplored. To address this gap, we introduce a novel Critical-Set Base-Surge (CSBS) policy, which combines a constant order policy for regular sources to meet ...
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作者：Elmachtoub, Adam N.; Kim, Hyemi
作者单位：Columbia University; Columbia University
摘要：Vehicle sharing systems, such as those for bicycles, scooters, and cars, are fundamental to serve transportation needs. Companies that operate these systems set prices (or fares) using algorithms to determine how much a user must pay and display the fares through mobile applications. This may result in users from different locations paying different prices for a vehicle. Moreover, the overall accessibility of these systems may be very different depending on the user's location. Platforms and r...
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作者：El Housni, Omar; Goyal, Vineet; Hanguir, Oussama; Stein, Clifford
作者单位：Cornell University; Columbia University
摘要：Matching demand (riders) to supply (drivers) efficiently is a fundamental problem for ride-sharing platforms that need to match the riders (almost) as soon as the request arrives with only partial knowledge about future ride requests. A myopic approach that computes an optimal matching for current requests ignoring future uncertainty can be highly suboptimal. In this paper, we consider a two-stage robust optimization framework for this matching problem in which future demand uncertainty is mod...
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作者：Feng, Yiding; Tang, Wei; Xu, Haifeng
作者单位：Hong Kong University of Science & Technology; Chinese University of Hong Kong; University of Chicago
摘要：We introduce and study the online Bayesian recommendation problem for a recommender system platform. The platform has the privilege to privately observe a utilityrelevant state of a product at each round and uses this information to make online recommendations to a stream of myopic users. This paradigm is common in a wide range of scenarios in the current internet economy. The platform commits to an online recommendation policy that utilizes its information advantage on the product state to pe...
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作者：Yan, Chiwei; Yan, Julia; Shen, Yifan
作者单位：University of California System; University of California Berkeley; University of British Columbia; University of Washington; University of Washington Seattle
摘要：Shared rides, which pool individual riders into a single vehicle, are essential for mitigating congestion and promoting more sustainable urban transportation. However, major ridesharing platforms have long struggled to maintain a healthy and profitable shared rides product. To understand why shared rides have struggled, we analyze procedures commonly used in practice to set static prices for shared rides and discuss their pitfalls. We then propose a pricing policy that is adaptive to matching ...
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作者：You, Zhengzhong; Yang, Yu; Wang, Xinshang; Yin, Wotao
作者单位：State University System of Florida; University of Florida; State University System of Florida; University of Florida
摘要：Branching is one of the most important components in branch-price-and-cut (BPC) algorithms for solving vehicle routing problems (VRPs) exactly. However, learning to branch is much more challenging in BPC than in branch-and-cut algorithms that are used for solving general mixed integer programs because branching, in this case, is generally performed by adding a dense constraint to the restricted master problem (RMP), and meanwhile, the variables in the RMP change constantly. To address such cha...
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作者：Liang, Yong; Mao, Xiaojie; Wang, Shiyuan
作者单位：Tsinghua University; Tsinghua University; Shanghai University of Finance & Economics
摘要：We study an online joint assortment-inventory optimization problem, in which we assume that the choice behavior of each customer follows the multinomial logit (MNL) choice model, and the attraction parameters are unknown a priori. The retailer makes periodic assortment and inventory decisions to dynamically learn from the customer choice observations about the attraction parameters while maximizing the expected total profit over time. In this paper, we propose a novel algorithm that can effect...
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作者：Anderson, Robert M.; Kim, Baeho; Ryu, Dean
作者单位：Harbin Institute of Technology; University of California System; University of California Berkeley; Korea University; Instituto Tecnologico Autonomo de Mexico
摘要：Estimated covariance and precision matrices of asset returns significantly influence the set of portfolios compliant with risk budgets and their potential losses. Statistical risk modeling approaches often assume temporal stability for consistency with a static factor structure, typically estimated within TM-250 days of data history, resulting in finitesample estimation error when the dimension of the population exceeds the number of observations. Our study investigates the application of Prin...
