Operations Research

最新文章

• Sequential Importance Sampling and Resampling for Dynamic Portfolio Credit Risk AI翻译
  作者：Deng, Shaojie; Giesecke, Kay; Lai, Tze Leung
  作者单位：Microsoft; Stanford University; Stanford University
  摘要：We provide a sequential Monte Carlo method for estimating rare-event probabilities in dynamic, intensity-based point process models of portfolio credit risk. The method is based on a change of measure and involves a resampling mechanism. We propose resampling weights that lead, under technical conditions, to a logarithmically efficient simulation estimator of the probability of large portfolio losses. A numerical analysis illustrates the features of the method and contrasts it with other rare-...
• Lower Bounds and Heuristics for Supply Chain Stock Allocation AI翻译
  作者：Marklund, Johan; Rosling, Kaj
  作者单位：Lund University; Linnaeus University
  摘要：Assume that in periods with stochastic demand remain until the next replenishment arrives at a central warehouse. How should the available inventory be allocated among N retailers? This paper presents a new policy and a new lower bound for the expected cost of this problem. The lower bound becomes tight as N -> infinity. The infinite horizon problem then decomposes into N independent m-period problems with optimal retailer ship-up-to levels that decrease over the in periods, and the warehouse ...
• A Branch-Price-and-Cut Algorithm for Single-Product Maritime Inventory Routing AI翻译
  作者：Engineer, Faramroze G.; Furman, Kevin C.; Nemhauser, George L.; Savelsbergh, Martin W. P.; Song, Jin-Hwa
  作者单位：University of Newcastle; Exxon Mobil Corporation; University System of Georgia; Georgia Institute of Technology
  摘要：A branch-price-and-cut algorithm is developed for a complex maritime inventory-routing problem with varying storage capacities and production/consumption rates at facilities. The resulting mixed-integer pricing problem is solved exactly and efficiently using a dynamic program that exploits certain extremal characteristics of the pricing problem. The formulation is tightened by using the problem's boundary conditions in preprocessing and to restrict the set of columns that are produced by the p...
• Polymatroid Optimization, Submodularity, and Joint Replenishment Games AI翻译
  作者：He, Simai; Zhang, Jiawei; Zhang, Shuzhong
  作者单位：City University of Hong Kong; New York University; University of Minnesota System; University of Minnesota Twin Cities
  摘要：In this paper we consider the problem of maximizing a separable concave function over a polymatroid. More specifically, we study the submodularity of its optimal objective value in the parameters of the objective function. This question is interesting in its own right and is encountered in many applications. But our research has been motivated mainly by a cooperative game associated with the well-known joint replenishment model. By applying our general results on polymatroid optimization, we p...
• On the Complexity of Nonoverlapping Multivariate Marginal Bounds for Probabilistic Combinatorial Optimization Problems AI翻译
  作者：Doan, Xuan Vinh; Natarajan, Karthik
  作者单位：University of Warwick; University of Warwick; City University of Hong Kong
  摘要：Given a combinatorial optimization problem with an arbitrary partition of the set of random objective coefficients, we evaluate the tightest-possible bound on the expected optimal value for joint distributions consistent with the given multivariate marginals of the subsets in the partition. For univariate marginals, this bound was first proposed by Meilijson and Nadas [Meilijson, I., A. Nadas. 1979. Convex majorization with an application to the length of critical path. J. Appl. Probab. 16(3) ...
• Price of Correlations in Stochastic Optimization AI翻译
  作者：Agrawal, Shipra; Ding, Yichuan; Saberi, Amin; Ye, Yinyu
  作者单位：Stanford University; Stanford University
  摘要：When decisions are made in the presence of high-dimensional stochastic data, handling joint distribution of correlated random variables can present a formidable task, both in terms of sampling and estimation as well as algorithmic complexity. A common heuristic is to estimate only marginal distributions and substitute joint distribution by independent (product) distribution. In this paper, we study possible loss incurred on ignoring correlations through a distributionally robust stochastic pro...
• Asymptotic Optimality of Balanced Routing AI翻译
  作者：Chen, Hong; Ye, Heng-Qing
  作者单位：Shanghai Jiao Tong University; Hong Kong Polytechnic University
  摘要：Consider a system with K parallel servers, each with its own waiting room. Upon arrival, a job is routed to the queue of one of the servers. Finding a routing policy that minimizes the total workload in the system is a known difficult problem in general. Even if the optimal policy is identified, the policy would require the full queue length information at the arrival of each job; for example, the join-the-shortest-queue policy (which is known to be optimal for identical servers with exponenti...
• Consistency of Multidimensional Convex Regression AI翻译
  作者：Lim, Eunji; Glynn, Peter W.
  作者单位：University of Miami; Stanford University
  摘要：Convex regression is concerned with computing the best fit of a convex function to a data set of n observations in which the independent variable is (possibly) multidimensional. Such regression problems arise in operations research, economics, and other disciplines in which imposing a convexity constraint on the regression function is natural. This paper studies a least-squares estimator that is computable as the solution of a quadratic program and establishes that it converges almost surely t...
• Sequential Correlated Equilibria in Stopping Games AI翻译
  作者：Heller, Yuval
  作者单位：University of Oxford; University of Oxford
  摘要：In many situations, such as trade in stock exchanges, agents have many opportunities to act within a short interval of time. The agents in such situations can often coordinate their actions in advance, but coordination during the game consumes too much time. An equilibrium in such situations has to be sequential in order to handle mistakes made by players. In this paper, we present a new solution concept for infinite-horizon dynamic games, which is appropriate for such situations: a sequential...
• A Copulas-Based Approach to Modeling Dependence in Decision Trees AI翻译
  作者：Wang, Tianyang; Dyer, James S.
  作者单位：Colorado State University System; Colorado State University Fort Collins; University of Texas System; University of Texas Austin
  摘要：This paper presents a general framework based on copulas for modeling dependent multivariate uncertainties through the use of a decision tree. The proposed dependent decision tree model allows multiple dependent uncertainties with arbitrary marginal distributions to be represented in a decision tree with a sequence of conditional probability distributions. This general framework could be naturally applied in decision analysis and real options valuations, as well as in more general applications...