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作者：Erazo, Ignacio; Toriello, Alejandro
作者单位：University System of Georgia; Georgia Institute of Technology
摘要：Motivated by applications in e-commerce logistics where orders or items arrive at different times and must be dispatched or processed in batches, we propose the subadditive dispatching problem (SAD), a strongly NP-hard problem defined by a set of orders with release times and a nondecreasing subadditive dispatch time function. A single uncapacitated vehicle must dispatch orders in batches to minimize the makespan, the time at which all orders have been dispatched. We propose a mixed-integer li...
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作者：Lu, Haihao; Yang, Jinwen
作者单位：Massachusetts Institute of Technology (MIT); University of Chicago
摘要：In this paper, we provide an affirmative answer to the long-standing question: Are GPUs useful in solving linear programming? We present cuPDLP.jl, a GPU implementation of restarted primal-dual hybrid gradient for solving linear programming (LP). We show that this prototype implementation in Julia has comparable numerical performance on standard LP benchmark sets to Gurobi, a highly optimized implementation of the simplex and interiorpoint methods. This demonstrates the power of using GPUs in ...
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作者：Lin, Yifan; Wang, Yuhao; Zhou, Enlu
作者单位：University System of Georgia; Georgia Institute of Technology
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：Wang, Yining; Liu, Quanquan
作者单位：University of Texas System; University of Texas Dallas
摘要：Personalized pricing with contextual information is a widespread practice in a number of revenue management problems. A pricing algorithm or platform utilizes users' personal data to make the most profitable pricing decisions, which could vary among individuals. In this paper, we study the question of estimating a contextual demand regression model with high-dimensional data, incorporating an unknown, nonparametric pricing function that acts as a confounding term to the demand model. We propos...
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作者：Guo, Siqi; Xiao, Fan; Liang, Zhe
作者单位：Tongji University; Shanghai University
摘要：It is widely acknowledged that deep dual-optimal inequalities (DDOIs) can stabilize the dual of a linear programming problem and accelerate its convergence. However, we find that adding DDOIs is not free but always comes with a price; that is, it increases the number of primal degenerate bases, and extra effort might be needed to achieve dual feasibility and prove its optimality. As a result, when addressing a linear programming problem, it is critical to stabilize the dual on the one hand, re...
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作者：Balkanski, Eric; Garimidi, Pranav; Gkatzelis, Vasilis; Schoepflin, Daniel; Tan, Xizhi
作者单位：Columbia University; Drexel University; Rutgers University System; Rutgers University New Brunswick
摘要：We revisit the well-studied problem of budget-feasible procurement, where a buyer with a strict budget constraint seeks to acquire services from a group of strategic providers (the sellers). During the last decade, several strategy-proof budget-feasible procurement auctions have been proposed, aiming to maximize the value of the buyer while eliciting each seller's true cost for providing their service. Our main result in this paper is a novel method for designing budget-feasible auctions, lead...
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作者：Bai, Yicheng; El Housni, Omar; Rusmevichientong, Paat; Topaloglu, Huseyin
作者单位：University of Southern California
摘要：We study a joint inventory stocking and assortment customization problem. We have access to a set of products that can be used to stock a storage facility with limited capacity. At the beginning of the selling horizon, we decide how many units of each product to stock. Customers of different types with type-dependent preferences for the products arrive over the selling horizon. Depending on the remaining product inventories and the type of the customer, we offer a product assortment to the arr...
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作者：Ba, Wenjia; Lin, Tianyi; Zhang, Jiawei; Zhou, Zhengyuan
作者单位：University of British Columbia; Columbia University; New York University
摘要：We consider online no-regret learning in unknown games with bandit feedback, where each player can only observe its reward at each time-determined by all players' current joint action-rather than its gradient. We focus on the class of smooth and strongly monotone games and study optimal no-regret learning therein. Leveraging self-concordant barrier functions, we first construct a new bandit learning algorithm and show that it root ffiffiffi achieves the single-agent optimal regret of Theta ( n...
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作者：Kannan, Rohit; Bayraksan, Guezin; Luedtke, James R.
作者单位：Virginia Polytechnic Institute & State University; University System of Ohio; Ohio State University; University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison
摘要：We study optimization for data-driven decision making when we have observations of the uncertain parameters within an optimization model together with concurrent observations of covariates. The goal is to choose a decision that minimizes the expected cost conditioned on a new covariate observation. We investigate two data-driven frameworks that integrate a machine learning prediction model within a stochastic programming sample average approximation (SAA) for approximating the solution to this...
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作者：Cohen, Maxime C.; Miao, Sentao; Wang, Yining
作者单位：McGill University; University of Colorado System; University of Colorado Boulder; University of Texas System; University of Texas Dallas
摘要：Following the increasing popularity of personalized pricing, there is a growing concern from customers and policymakers regarding fairness considerations. This paper studies the problem of dynamic pricing with unknown demand under two types of fairness constraints: price fairness and demand fairness. For price fairness, the retailer is required to (i) set similar prices for different customer groups (called group fairness) and (ii) ensure that the prices over time for each customer group are r...
