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作者：Chen, Rui; Gunluk, Oktay; Lodi, Andrea
作者单位：Cornell University
摘要：Dantzig-Wolfe (DW) decomposition is a well-known technique in mixedinteger programming (MIP) for decomposing and convexifying constraints to obtain potentially strong dual bounds. We investigate cutting planes that can be derived using the DW decomposition algorithm and show that these cuts can provide the same dual bounds as DW decomposition. More precisely, we generate one cut for each DW block, and when combined with the constraints in the original formulation, these cuts imply the objectiv...
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作者：Zhen, Jianzhe; Kuhn, Daniel; Wiesemann, Wolfram
作者单位：Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; Imperial College London
摘要：Robust optimization and distributionally robust optimization are modeling paradigms for decision making under uncertainty where the uncertain parameters are only known to reside in an uncertainty set or are governed by any probability distribution from within an ambiguity set, respectively, and a decision is sought that minimizes a cost function under the most adverse outcome of the uncertainty. In this paper, we develop a rigorous and general theory of robust and distributionally robust nonli...
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作者：Curmei, Mihaela; Hall, Georgina
作者单位：University of California System; University of California Berkeley; INSEAD Business School
摘要：We present a hierarchy of semidefinite programs (SDPs) for the problem of fitting a shape-constrained (multivariate) polynomial to noisy evaluations of an unknown shape-constrained function. These shape constraints include convexity or monotonicity over a box. We show that polynomial functions that are optimal to any fixed level of our hierarchy form a consistent estimator of the underlying shape-constrained function. As a by-product of the proof, we establish that sum of squares-convex polyno...
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作者：Miao, Sentao; Wang, Yining; Zhang, Tiawei
作者单位：University of Colorado System; University of Colorado Boulder; University of Texas System; University of Texas Dallas; New York University
摘要：This paper proposes an approach that can be applied to solve several important revenue management (RM) problems with demand learning and potentially large action space constrained by initial unreplenishable resources. This approach combines the technique of the primal-dual method in optimization and upper confidence bound algorithm in learning. Three important RM problems are studied in this paper: network revenue management, dynamic assortment selection with a multinomial-logit choice model, ...
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作者：Berczi, Kristof; Codazzi, Laura; Golak, Julian; Grigoriev, Alexander
作者单位：Eotvos Lorand University; Eotvos Lorand University; Hamburg University of Technology; University of Hamburg; Maastricht University
摘要：In combinatorial markets, the goal is typically to determine a pair of pricing and allocation of items that results in an efficient distribution of resources or maximizes the seller's profit. In dynamic pricing schemes, agents arrive in an unspecified sequential order, and the prices can be updated between agent arrivals, which makes the concept fairness of dynamic prices highly nontrivial. In markets with expected price deflation, typical agent follows the prices prior to their purchase and b...
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作者：Veraart, Luitgard Anna Maria; Zhang, Yuliang
作者单位：University of London; London School Economics & Political Science
摘要：We analyse how post-trade netting in over-the-counter derivatives markets affects systemic risk. In particular, we focus on two post-trade netting services that rely on multilateral netting techniques: portfolio rebalancing and portfolio compression. First, we provide mathematical characterisations of their netting mechanisms and explain their relationship. Then, we analyse the effects of post-trade netting from a network perspective by considering contagion arising from defaults on variation ...
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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：Su, Weijie
作者单位：University of Pennsylvania
摘要：Machine learning (ML) and artificial intelligence (AI) conferences including NeurIPS is Neural Information Processing Systems and International Conference on Machine Learning have experienced a significant decline in peer review quality in recent years. To address this growing challenge, we introduce the isotonic mechanism, a computationally efficient approach to enhancing the accuracy of noisy review scores by incorporating authors' private assessments of their submissions. Under this mechani...
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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：Jiang, Zhaohui (Zoey); Li, Jun
作者单位：Carnegie Mellon University; University of Michigan System; University of Michigan
摘要：Accurate operational decisions require precise knowledge of the causal effects of such decisions on outcomes, a task that becomes increasingly complex in dynamic business environments. We propose an idea of instrumenting while experimenting, whereby researchers can create their own instruments by injecting small, random variations directly into the decision-making process and then use such variations to obtain causal estimates of the impact of varying business decisions at scale without disrup...
