4期

最新文章

• Contextual Search in the Presence of Adversarial Corruptions AI翻译
  作者：Krishnamurthy, Akshay; Lykouris, Thodoris; Podimata, Chara; Schapire, Robert
  作者单位：Microsoft; Massachusetts Institute of Technology (MIT); University of California System; University of California Berkeley
  摘要：We study contextual search, a generalization of binary search in higher dimensions, which captures settings such as feature-based dynamic pricing. Standard formulations of this problem assume that agents act in accordance with a specific homogeneous response model. In practice, however, some responses may be adversarially corrupted. Existing algorithms heavily depend on the assumed responsemodel being (approximately) accurate for all agents and have poor performance in the presence of even a f...
• Technical Note-New Bounds for Cardinality-Constrained Assortment Optimization Under the Nested Logit Model AI翻译
  作者：Kunnumkal, Sumit
  作者单位：Indian School of Business (ISB)
  摘要：We consider the cardinality-constrained assortment optimization problem under the nested logit model where there is a constraint that limits the number of products that can be offered within each nest. The problem is known to be intractable if the nest dissimilarity parameters are larger than one or there is a no-purchase alternative within each nest. Although these conditions often come up in practice, the existing solution approaches cannot handle them. We propose a solution method to obtain...
• Economic Behavior of Information Acquisition: Impact on Peer Grading in Massive Open Online Courses AI翻译
  作者：Yoo, Onesun Steve; Zhan, Dongyuan
  作者单位：University of London; University College London
  摘要：A critical issue in operating massive open online courses (MOOCs) is the scalability of providing feedback. Because it is not feasible for instructors to grade a large number of students' assignments, MOOCs use peer grading systems. This study investigates the efficacy of that practice when student graders are rational economic agents. We characterize grading as a process of (a) acquiring information to assess an assignment's quality and (b) reporting a score. This process entails a tradeoff b...
• Product Ranking in the Presence of Social Learning AI翻译
  作者：Maglaras, Costis; Scarsini, Marco; Shin, Dongwook; Vaccarid, Stefano
  作者单位：Columbia University; Luiss Guido Carli University; Hong Kong University of Science & Technology
  摘要：This paper studies product ranking mechanisms of a monopolistic online platform in the presence of social learning. The products' quality is initially unknown, but consumers can sequentially learn it as online reviews accumulate. A salient aspect of our problem is that consumers, who want to purchase a product from a list of items displayed by the platform, incur a search cost while scrolling down the list. In this setting, the social learning dynamics, and hence the demand, is affected by the...
• Optimization-Based Scenario Reduction for Data-Driven Two-Stage Stochastic Optimization AI翻译
  作者：Bertsimas, Dimitris; Mundru, Nishanth
  作者单位：Massachusetts Institute of Technology (MIT)
  摘要：We propose a novel, optimization-based method that takes into account the objective and problem structure for reducing the number of scenarios, m, needed for solving two-stage stochastic optimization problems. We develop a corresponding convex optimization-based algorithm and show that, as the number of scenarios increase, the proposed method recovers the SAA solution. We report computational results with both synthetic and real-world data sets that show that the proposed method has significan...
• Production Planning with Risk Hedging Under a Conditional Value at Risk Objective AI翻译
  作者：Wang, Liao; Yao, David D.
  作者单位：University of Hong Kong; Columbia University
  摘要：A central problem in planning production capacity is how to effectively manage demand risk. We develop a model that integrates capacity planning and risk hedging decisions under a popular risk measure, conditional value at risk (CVaR). The CVaR objective generalizes the usual risk-neutral objective (such as the expected payoff) and allows for explicit modeling of the degree of aversion to downside risk (associated with low demand). The starting point of our model is to incorporate the impact o...
• Voxel-Based Solution Approaches to the Three-Dimensional Irregular Packing Problem AI翻译
  作者：Lamas-Fernandez, Carlos; Bennell, Julia A.; Martinez-Sykora, Antonio
  作者单位：Solent University; University of Southampton; University of Leeds
  摘要：Research on the three-dimensional (3D) packing problem has largely focused on packing boxes for the transportation of goods. As a result, there has been little focus on packing irregular shapes in the operational research literature. New technologies have raised the practical importance of 3D irregular packing problems and the need for efficient solutions. In this work, we address the variant of the problem where the aim is to place a set of 3D irregular items in a container, while minimizing ...
• The Stability of MNL-Based Demand Under Dynamic Customer Substitution and Its Algorithmic Implications AI翻译
  作者：Aouad, Ali; Segev, Danny
  作者单位：University of London; London Business School; Tel Aviv University
  摘要：We study the dynamic assortment planning problem under the widely utilized multinomial logit choice model (MNL). In this single-period assortment optimization and inventory management problem, the retailer jointly decides on an assortment, that is, a sub-set of products to be offered, as well as on the inventory levels of these products, aiming to maximize the expected revenue subject to a capacity constraint on the total number of units stocked. The demand process is formed by a stochastic st...
• Learning Product Rankings Robust to Fake Users AI翻译
  作者：Golrezaei, Negin; Manshadi, Vahideh; Schneider, Jon; Sekard, Shreyas
  作者单位：Massachusetts Institute of Technology (MIT); Yale University; Alphabet Inc.; Google Incorporated; University of Toronto; University Toronto Scarborough; University of Toronto
  摘要：In many online platforms, customers' decisions are substantially influenced by product rankings as most customers only examine a few top-ranked products. This induces a race for visibility among sellers, who may be incentivized to artificially inflate their position by employing fake users as exemplified by the emergence of click farms. Motivated by such fraudulent behavior, we study the problem of learning product rankings when a platform faces a mixture of real and fake users who are indisti...
• Technical Note-Bidding in Multidimensional Auctions When the Qualities of All Bidders Matter AI翻译
  作者：Lorentziadis, Panos L.
  作者单位：Athens University of Economics & Business
  摘要：In multidimensional auctions, bidders compete in both quality and price, which are combined by a score rule. A well-known problem in procurement management is that nonprice attributes are often poorly measured and unreliably estimated. Adjustments of the reported quality based on the qualities of rival bids can enhance the reliability of the measurement process. We develop a general model of score function that is dependent on the qualities offered by all bidders who differ in terms of their p...