Operations Research

最新文章

• On Incomplete Learning and Certainty-Equivalence Control AI翻译
  作者：Keskin, N. Bora; Zeevi, Assaf
  作者单位：Duke University; Columbia University
  摘要：We consider a dynamic learning problem where a decision maker sequentially selects a control and observes a response variable that depends on chosen control and an unknown sensitivity parameter. After every observation, the decision maker updates his or her estimate of the unknown parameter and uses a certainty-equivalence decision rule to determine subsequent controls based on this estimate. We show that under this certainty-equivalence learning policy the parameter estimates converge with po...
• Approximation Algorithms for a Class of Stochastic Selection Problems with Reward and Cost Considerations AI翻译
  作者：Strinka, Zohar M. A.; Romeijn, H. Edwin
  作者单位：University System of Georgia; Georgia Institute of Technology
  摘要：We study a class of problems with both binary selection decisions and associated continuous choices that result in stochastic rewards and costs. The rewards are received based on the decision maker's selection, and the costs depend both on the decisions and realizations of the stochastic variables. We consider a family of risk-based objective functions that contains the traditional risk-neutral expected-value objective as a special case. A combination of rounding and sample average approximati...
• Supply and Demand Functions in Inventory Models AI翻译
  作者：Feng, Qi; Shanthikumar, J. George
  作者单位：Purdue University System; Purdue University
  摘要：The central issue in supply chain management is to match supply with demand, and the heart of a planning model is the modeling of supply and demand functions. To allow for analytical tractability, the existing literature often assumes almost surely linear supply and demand functions, which greatly limits the applicability of the models. The goal of this paper is to provide a unified approach to analyze general random supply and demand functions. By transforming the problem into one defined on ...
• Static Routing in Stochastic Scheduling: Performance Guarantees and Asymptotic Optimality AI翻译
  作者：Balseiro, Santiago R.; Brown, David B.; Chen, Chen
  作者单位：Columbia University; Duke University
  摘要：We study the problem of scheduling a set of J jobs on M machines with stochastic job processing times when no preemptions are allowed and with a weighted sum of expected completion times objective. Our model allows for unrelated machines: the distributions of processing times may vary across both jobs and machines. We study static routing policies, which assign (or route) each job to a particular machine at the start of the problem and then sequence jobs on each machine according to the weight...
• On the Optimality of Three-Part Tariff Plans: When Does Free Allowance Matter? AI翻译
  作者：Bhargava, Hemant K.; Gangwar, Manish
  作者单位：University of California System; University of California Davis; Indian School of Business (ISB)
  摘要：Two- (2PTs) and three-part tariffs (3PTs) are widely used for selling goods, to compensate workers, and in procurement contracts. They are practical alternatives to complex nonlinear tariffs in on-demand services and technology industries and are more profitable than the restrictive per-unit and unlimited-use pricing. A 2PT imposes both a fixed (access) fee and a per-unit (usage) fee, and a 3PT generalizes it by bundling some free units (an allowance) into the fixed fee. Intuitively, bundling ...
• The First Approximation Algorithm for the Maximin Latin Hypercube Design Problem AI翻译
  作者：Le Guiban, Kaourintin; Rimmel, Arpad; Weisser, Marc-Antoine; Tomasik, Joanna
  作者单位：Universite Paris Saclay
  摘要：In metamodeling, the choice of sampling points is crucial for the quality of the model. In this context, the maximin Latin hypercube designs (LHD), with their space-filling and noncollapsing properties, are particularly efficient. To this day, there is no polynomial time algorithm that produces optimal maximin LHDs, i.e., in which the minimum distance between two points (the separation distance) is maximal. We are interested in LHDs with a separation distance as large as possible. The algorith...
• Effects of System Parameters on the Optimal Cost and Policy in a Class of Multidimensional Queueing Control Problems AI翻译
  作者：Vercraene, Samuel; Gayon, Jean-Philippe; Karaesmen, Fikri
  作者单位：Institut National des Sciences Appliquees de Lyon - INSA Lyon; Communaute Universite Grenoble Alpes; Institut National Polytechnique de Grenoble; Universite Grenoble Alpes (UGA); Centre National de la Recherche Scientifique (CNRS)
  摘要：We consider a class of Markov Decision Processes frequently employed to model queueing and inventory control problems. For these problems, we explore how changes in different system input parameters (transition rates, costs, discount rates etc.) affect the optimal cost and the optimal policy when the state space of the problem is multidimensional. To address a large class of problems, we introduce two generic dynamic programming operators to model different types of controlled events. For thes...
• Optimizing the Geometry of Wildlife Corridors in Conservation Reserve Design AI翻译
  作者：St John, Rachel; Toth, Sandor F.; Zabinsky, Zelda B.
  作者单位：University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle
  摘要：Wildlife corridors are often used to connect critical habitat for species protection. Mixed integer programming models have been used in the past to create wildlife corridors, but they lack the capacity to control corridor geometry. We propose an approach that employs path planning techniques from artificial intelligence to account for and control corridor geometry, such as width and length. By combining path planning with network optimization, our approach allows the user to control and optim...
• Technical Note-A Conic Integer Optimization Approach to the Constrained Assortment Problem Under the Mixed Multinomial Logit Model AI翻译
  作者：Sen, Alper; Atamturk, Alper; Kaminsky, Philip
  作者单位：Ihsan Dogramaci Bilkent University; University of California System; University of California Berkeley
  摘要：We consider the constrained assortment optimization problem under the mixed multinomial logit model. Even moderately sized instances of this problem are challenging to solve directly using standard mixed-integer linear optimization formulations. This has motivated recent research exploring customized optimization strategies and approximation techniques. In contrast, we develop a novel conic quadratic mixed-integer formulation. This new formulation, together with McCormick inequalities exploiti...
• Inverse Optimization with Noisy Data AI翻译
  作者：Aswani, Anil; Shen, Zuo-Jun (Max); Siddiq, Auyon
  作者单位：University of California System; University of California Berkeley; University of California System; University of California Berkeley; University of California System; University of California Berkeley; University of California System; University of California Los Angeles
  摘要：Inverse optimization refers to the inference of unknown parameters of an optimization problem based on knowledge of its optimal solutions. This paper considers inverse optimization in the setting where measurements of the optimal solutions of a convex optimization problem are corrupted by noise. We first provide a formulation for inverse optimization and prove it to be NP-hard. In contrast to existing methods, we show that the parameter estimates produced by our formulation are statistically c...