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作者:Arts, Joachim; Basten, Rob; Van Houtum, Geert-Jan
作者单位:Eindhoven University of Technology
摘要:We consider a single stock-point for a repairable item facing Markov modulated Poisson demand. Repair of failed parts may be expedited at an additional cost to receive a shorter lead time. Demand that cannot be filled immediately is backordered and penalized. The manager decides on the number of spare repairables to purchase and on the expediting policy. We characterize the optimal expediting policy using a Markov decision process formulation and provide closed-form necessary and sufficient co...
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作者:Cont, Rama; Duffie, Darrell; Glasserman, Paul; Rogers, Chris; Vega-Redondo, Fernando
作者单位:Imperial College London; Stanford University; Columbia University; University of Cambridge; Bocconi University
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作者:Kley, Oliver; Klueppelberg, Claudia; Reinert, Gesine
作者单位:Technical University of Munich; University of Oxford
摘要:We model the influence of sharing large exogeneous losses to the reinsurance market by a bipartite graph. Using Paretotailed claims and multivariate regular variation we obtain asymptotic results for the value-at-risk and the conditional tail expectation. We show that the dependence on the network structure plays a fundamental role in their asymptotic behaviour. As is well known in a nonnetwork setting, if the Pareto exponent is larger than 1, then for the individual agent (reinsurance company...
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作者:Banerjee, Siddhartha; Sanghavi, Sujay; Shakkottai, Sanjay
作者单位:Cornell University; University of Texas System; University of Texas Austin
摘要:Existing approaches to designing recommendation systems with user feedback focus on settings where the number of items is small and/or admit some underlying structure. It is unclear, however, if these approaches extend to applications like social network news feeds and content-curation platforms, which have large and unstructured content pools and constraints on user-item recommendations. To this end, we consider the design of recommendation systems in content-rich setting-where the number of ...
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作者:Alizamir, Saed; de Vericourt, Francis; Sun, Peng
作者单位:Yale University; European School of Management & Technology; Duke University
摘要:Feed-in-tariff (FIT) policies aim at driving down the cost of renewable energy by fostering learning and accelerating the diffusion of green technologies. Under FIT mechanisms, governments purchase green energy at tariffs that are set above market price. The success or failure of FIT policies, in turn, critically depend on how these tariffs are determined and adjusted over time. This paper provides insights into designing cost-efficient and socially optimal FIT programs. Our modeling framework...
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作者:Bauschke, Heinz H.; Koch, Valentin R.; Phan, Hung M.
作者单位:University of British Columbia; Autodesk, Inc.; University of Massachusetts System; University of Massachusetts Lowell
摘要:The basic optimization problem of road design is quite challenging due to an objective function that is the sum of nonsmooth functions and the presence of set constraints. In this paper, we model and solve this problem by employing the Douglas-Rachford splitting algorithm. This requires a careful study of new proximity operators related to minimizing area and to the stadium norm. We compare our algorithm to a state-of-the-art projection algorithm. Our numerical results illustrate the potential...
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作者:Koshal, Jayash; Nedic, Angelia; Shanbhag, Uday V.
作者单位:University of Illinois System; University of Illinois Urbana-Champaign; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要:We consider a class of Nash games, termed as aggregative games, being played over a networked system. In an aggregative game, a player's objective is a function of the aggregate of all the players' decisions. Every player maintains an estimate of this aggregate, and the players exchange this information with their local neighbors over a connected network. We study distributed synchronous and asynchronous algorithms for information exchange and equilibrium computation over such a network. Under...
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作者:Thanh Nguyen; Subramanian, Vijay; Berry, Randall
作者单位:Purdue University System; Purdue University; University of Michigan System; University of Michigan; Northwestern University
摘要:We study decentralized markets involving producers and consumers that are facilitated by middlemen. We do this by analyzing a noncooperative networked bargaining game. We assume a complete information setup wherein all the agents know the structure of the network, the values of the consumers, and the transaction costs involved but allow for some search friction when either producers or consumers trade with middlemen. In such a setting, we show that sunk cost problems and a heterogeneous networ...
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作者:Angelus, Alexandar; Ozer, Ozalp
作者单位:University of Texas System; University of Texas Dallas
摘要:We consider a nonstationary, stochastic, multistage supply system with a general assembly structure, in which customers can place orders in advance of their future demand requirements. This advance demand information is now recognized in both theory and practice as an important strategy for managing the mismatch between supply and demand. In conjunction, we allow expediting of components and partially completed subassemblies in the system to provide the supply chain with the means to manage th...
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作者:Nobibon, Fabrice Talla; Cherchye, Laurens; Crama, Yves; Demuynck, Thomas; De Rock, Bram; Spieksma, Frits C. R.
作者单位:KU Leuven; University of Liege; Maastricht University; Universite Libre de Bruxelles; KU Leuven
摘要:This paper focuses on revealed preference tests of the collective model of household consumption. We start by showing that the decision problems corresponding to testing collective rationality are NP-complete. This makes the application of these tests problematic for (increasingly available) large(r)-scale data sets. We then present two approaches to overcome this negative result. First, we introduce exact algorithms based on mixed-integer programming (MIP) formulations of the collective ratio...