2016

最新文章

• Preferences, Homophily, and Social Learning AI翻译
  作者：Lobel, Ilan; Sadler, Evan
  作者单位：New York University
  摘要：We study a sequential model of Bayesian social learning in networks in which agents have heterogeneous preferences, and neighbors tend to have similar preferences-a phenomenon known as homophily. We find that the density of network connections determines the impact of preference diversity and homophily on learning. When connections are sparse, diverse preferences are harmful to learning, and homophily may lead to substantial improvements. In contrast, in a dense network, preference diversity i...
• Optimizing Flow Thinning Protection in Multicommodity Networks with Variable Link Capacity AI翻译
  作者：Pioro, Michal; Fouquet, Yoann; Nace, Dritan; Poss, Michael
  作者单位：Warsaw University of Technology; Lund University; Sorbonne Universite; Universite de Technologie de Compiegne; Universite de Montpellier
  摘要：Flow thinning (FT) is a concept of a traffic routing and protection strategy applicable to communication networks with variable capacity of links. In such networks, the links do not attain their nominal (maximum) capacity simultaneously, so in a typical network state only some links are fully available whereas on each of the remaining links only a fraction of its maximum capacity is usable. Every end-to-end traffic demand is assigned a set of logical tunnels whose total capacity is dedicated t...
• Online Discrete Optimization in Social Networks in the Presence of Knightian Uncertainty AI翻译
  作者：Raginsky, Maxim; Nedic, Angelia
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign
  摘要：We study a model of collective real-time decision making (or learning) in a social network operating in an uncertain environment, for which no a priori probabilistic model is available. Instead, the environment's impact on the agents in the network is seen through a sequence of cost functions, revealed to the agents in a causal manner only after all the relevant actions are taken. There are two kinds of costs: individual costs incurred by each agent and local-interaction costs incurred by each...
• Large-Scale Loan Portfolio Selection AI翻译
  作者：Sirignano, Justin A.; Tsoukalas, Gerry; Giesecke, Kay
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University of Pennsylvania; Stanford University
  摘要：We consider the problem of optimally selecting a large portfolio of risky loans, such as mortgages, credit cards, auto loans, student loans, or business loans. Examples include loan portfolios held by financial institutions and fixed-income investors as well as pools of loans backing mortgage-and asset-backed securities. The size of these portfolios can range from the thousands to even hundreds of thousands. Optimal portfolio selection requires the solution of a high-dimensional non linearinte...
• A Cycle-Based Formulation and Valid Inequalities for DC Power Transmission Problems with Switching AI翻译
  作者：Kocuk, Burak; Jeon, Hyemin; Dey, Santanu S.; Linderoth, Jeff; Luedtke, James; Sun, Xu Andy
  作者单位：University System of Georgia; Georgia Institute of Technology; University of California System; University of California Berkeley; University of Wisconsin System; University of Wisconsin Madison
  摘要：It is well known that optimizing network topology by switching on and off transmission lines improves the efficiency of power delivery in electrical networks. In fact, the USA Energy Policy Act of 2005 (Section 1223) states that the United States should encourage, as appropriate, the deployment of advanced transmission technologies including optimized transmission line configurations. As such, many authors have studied the problem of determining an optimal set of transmission lines to switch o...
• Mitigating Uncertainty via Compromise Decisions in Two-Stage Stochastic Linear Programming: Variance Reduction AI翻译
  作者：Sen, Suvrajeet; Liu, Yifan
  作者单位：University of Southern California
  摘要：Stochastic Programming (SP) has long been considered a well-justified yet computationally challenging paradigm for practical applications. Computational studies in the literature often involve approximating a large number of scenarios by using a small number of scenarios to be processed via deterministic solvers, or running Sample Average Approximation on some genre of high performance machines so that statistically acceptable bounds can be obtained. In this paper we show that for a class of s...
• Joint Inventory and Markdown Management for Perishable Goods with Strategic Consumer Behavior AI翻译
  作者：Hu, Peng; Shum, Stephen; Yu, Man
  作者单位：Huazhong University of Science & Technology; City University of Hong Kong; Hong Kong University of Science & Technology
  摘要：In this paper we formulate and analyze a novel model on a firm's dynamic inventory and markdown decisions for perishable goods. We consider a dynamic stochastic setting, where every period consists of two phases, clearance phase and regular-sales phase. In the clearance phase, the firm decides how much to order for regular sales, as well as whether to markdown some (or all) of the leftover inventory from the previous period that will be disposed otherwise. Since strategic consumers may buy the...
• Decomposable Markov Decision Processes: A Fluid Optimization Approach AI翻译
  作者：Bertsimas, Dimitris; Misic, Velibor V.
  作者单位：Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT); University of California System; University of California Los Angeles
  摘要：Decomposable Markov decision processes (MDPs) are problems where the stochastic system can be decomposed into multiple individual components. Although such MDPs arise naturally in many practical applications, they are often difficult to solve exactly due to the enormous size of the state space of the complete system, which grows exponentially with the number of components. In this paper, we propose an approximate solution approach to decomposable MDPs that is based on re-solving a fluid linear...
• Multistage Robust Mixed-Integer Optimization with Adaptive Partitions AI翻译
  作者：Bertsimas, Dimitris; Dunning, Iain
  作者单位：Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT)
  摘要：We present a new partition-and-bound method for multistage adaptive mixed-integer optimization (AMIO) problems that extends previous work on finite adaptability. The approach analyzes the optimal solution to a static (nonadaptive) version of an AMIO problem to gain insight into which regions of the uncertainty set are restricting the objective function value. We use this information to construct partitions in the uncertainty set, leading to a finitely adaptable formulation of the problem. We u...
• Optimal Cost-Sharing in General Resource Selection Games AI翻译
  作者：Gkatzelis, Vasilis; Kollias, Konstantinos; Roughgarden, Tim
  作者单位：Stanford University; Stanford University
  摘要：Resource selection games provide a model for a diverse collection of applications where a set of resources is matched to a set of demands. Examples include routing in traffic and in telecommunication networks, service of requests on multiple parallel queues, and acquisition of services or goods with demand-dependent prices. In reality, demands are often submitted by selfish entities (players) and congestion on the resources results in negative externalities for their users. We consider a polic...