Operations Research

最新文章

• Dynamic Equilibria in Fluid Queueing Networks AI翻译
  作者：Cominetti, Roberto; Correa, Jose; Larre, Omar
  作者单位：Universidad de Chile
  摘要：Flows over time provide a natural and convenient description for the dynamics of a continuous stream of particles traveling from a source to a sink in a network, allowing to track the progress of each infinitesimal particle along time. A basic model for the propagation of flow is the so-called fluid queue model in which the time to traverse an edge is composed of a flow-dependent waiting time in a queue at the entrance of the edge plus a constant travel time after leaving the queue. In a dynam...
• The Post-Disaster Debris Clearance Problem Under Incomplete Information AI翻译
  作者：Celik, Melih; Ergun, Ozlem; Keskinocak, Pinar
  作者单位：Middle East Technical University; Northeastern University; University System of Georgia; Georgia Institute of Technology
  摘要：Debris management is one of the most time consuming and complicated activities among post-disaster operations. Debris clearance is aimed at pushing the debris to the sides of the roads so that relief distribution and search-and-rescue operations can be maintained in a timely manner. Given the limited resources, uncertainty, and urgency during disaster response, efficient and effective planning of debris clearance to achieve connectivity between relief demand and supply is important. In this pa...
• Demand Estimation and Ordering Under Censoring: Stock-Out Timing Is (Almost) All You Need AI翻译
  作者：Jain, Aditya; Rudi, Nils; Wang, Tong
  作者单位：Indian School of Business (ISB); INSEAD Business School; National University of Singapore
  摘要：Retailers facing uncertain demand can use observed sales to update demand estimates. However, such learning is limited by the amount of inventory carried; when demand exceeds inventory (i.e., when a stock-out event occurs), a retailer in general cannot observe actual demand. We propose using observations on the timing of sales occurrences in a Bayesian fashion to learn about demand, and we analyze this learning method for a multiperiod newsvendor setting. We find that, as previously shown with...
• The Benefit of Introducing Variability in Single-Server Queues with Application to Quality-Based Service Domains AI翻译
  作者：Xu, Ying; Scheller-Wolf, Alan; Sycara, Katia
  作者单位：Carnegie Mellon University; Carnegie Mellon University
  摘要：We propose a static service differentiation policy for a single-server queueing system serving homogeneous customers. We show that by randomly assigning customers different service grades with different service rates, the average waiting time can be reduced without affecting the mean service time. Such differentiation introduces more service time variability, but it also creates information that enables the implementation of service rate-based scheduling, which mitigates the increased variance...
• Improving Community Cohesion in School Choice via Correlated-Lottery Implementation AI翻译
  作者：Ashlagi, Itai; Shi, Peng
  作者单位：Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT)
  摘要：In school choice, children submit a preference ranking over schools to a centralized assignment algorithm, which takes into account schools' priorities over children and uses randomization to break ties. One criticism of existing school choice mechanisms is that they tend to disperse communities, so children do not go to school with others from their neighborhood. We suggest improving community cohesion by implementing a correlated lottery in a given school choice mechanism: we find a convex c...
• Stability and Endogenous Formation of Inventory Transshipment Networks AI翻译
  作者：Fang, Xin; Cho, Soo-Haeng
  作者单位：Singapore Management University; Carnegie Mellon University
  摘要：This paper studies a cooperative game of inventory transshipment among multiple firms. In this game, firms first make their inventory decisions independently and then decide collectively how to transship excess inventories to satisfy unmet demands. In modeling transshipment, we use networks of firms as the primitive, which offer a richer representation of relationships among firms by taking the coalitions used in all previous studies as special cases. For any given cooperative network, we cons...
• Technical Note-Joint Inventory and Pricing Control with General Additive Demand AI翻译
  作者：Chen, Hong; Zhang, Zhan
  作者单位：Shanghai Jiao Tong University; University of British Columbia
  摘要：This paper analyzes a periodic-review, joint inventory and pricing control problem for a firm that faces stochastic, price-sensitive demand under a nonstationary environment with fixed ordering costs. Any unsatisfied demand is backlogged. The objective is to maximize expected profit over a finite selling horizon by coordinating the inventory and pricing decisions in each period. We show that for an additive demand model, an (s, S, p) policy is optimal when the expected revenue is quasi-concave...
• The Value of Stochastic Modeling in Two-Stage Stochastic Programs with Cost Uncertainty AI翻译
  作者：Delage, Erick; Arroyo, Sharon; Ye, Yinyu
  作者单位：Universite de Montreal; HEC Montreal; Boeing; Stanford University
  摘要：Although stochastic programming is probably the most effective framework for handling decision problems that involve uncertain variables, it is always a costly task to formulate the stochastic model that accurately embodies our knowledge of these variables. In practice, this might require one to collect a large amount of observations, to consult with experts of the specialized field of practice, or to make simplifying assumptions about the underlying system. When none of these options seem fea...
• Information Relaxations, Duality, and Convex Stochastic Dynamic Programs AI翻译
  作者：Brown, David B.; Smith, James E.
  作者单位：Duke University
  摘要：We consider the information relaxation approach for calculating performance bounds for stochastic dynamic programs (DPs). This approach generates performance bounds by solving problems with relaxed nonanticipativity constraints and a penalty that punishes violations of these nonanticipativity constraints. In this paper, we study DPs that have a convex structure and consider gradient penalties that are based on first-order linear approximations of approximate value functions. When used with per...
• A Bayesian Framework for Quantifying Uncertainty in Stochastic Simulation AI翻译
  作者：Xie, Wei; Nelson, Barry L.; Barton, Russell R.
  作者单位：Rensselaer Polytechnic Institute; Northwestern University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
  摘要：When we use simulation to estimate the performance of a stochastic system, the simulation often contains input models that were estimated from real-world data; therefore, there is both simulation and input uncertainty in the performance estimates. In this paper, we provide a method to measure the overall uncertainty while simultaneously reducing the influence of simulation estimation error due to output variability. To reach this goal, a Bayesian framework is introduced. We use a Bayesian post...