Operations Research

最新文章

• Demand Shaping Through Bundling and Product Configuration: A Dynamic Multiproduct Inventory-Pricing Model AI翻译
  作者：Song, Jing-Sheng; Xue, Zhengliang
  作者单位：Duke University; International Business Machines (IBM); IBM USA
  摘要：In today's digital age, with the aid of the internet and data mining, many firms use vertically differentiated product bundling to influence demand to match up with inventory status, especially in industries with short product life cycles. Despite this practice, there is little understanding on how exactly the inventory dynamics impact the bundling strategy and, in turn, how the bundling strategy affects the firm's inventory decisions. To fill this gap, we present a dynamic model to analyze th...
• Duopoly Competition with Network Effects in Discrete Choice Models AI翻译
  作者：Chen, Ningyuan; Chen, Ying-Ju
  作者单位：University of Toronto; Hong Kong University of Science & Technology; Hong Kong University of Science & Technology
  摘要：We consider two firms selling products to a market of network-connected customers. Each firm is selling one product, and the two products are substitutable. The customers make purchases based on the multinomial logit model, and the firms compete for their purchasing probabilities. We characterize possible Nash equilibria for homogeneous network interactions and identical firms: When the network effects are weak, there is a symmetric equilibrium that the two firms evenly split the market; when ...
• Technical Note-Joint Learning and Optimization of Multi-Product Pricing with Finite Resource Capacity and Unknown Demand Parameters AI翻译
  作者：Chen, Qi (George); Jasin, Stefanus; Duenyas, Izak
  作者单位：University of London; London Business School; University of Michigan System; University of Michigan
  摘要：We consider joint learning and pricing in network revenue management (NRM) with multiple products, multiple resources with finite capacity, parametric demand model, and a continuum set of feasible price vectors. We study the setting with a general parametric demand model and the setting with a well-separated demand model. For the general parametric demand model, we propose a heuristic that is rate-optimal (i.e., its regret bound exactly matches the known theoretical lower bound under any feasi...
• Patient-Type Bayes-Adaptive Treatment Plans AI翻译
  作者：Skandari, M. Reza; Shechter, Steven M.
  作者单位：Imperial College London; University of British Columbia
  摘要：Patient heterogeneity in disease progression is prevalent in many settings. Treatment decisions that explicitly consider this heterogeneity can lower the cost of care and improve outcomes by providing the right care for the right patient at the right time. In this paper, we analyze the problem of designing ongoing treatment plans for a population with heterogeneity in disease progression and response to medical interventions. We create a model that learns the patient type by monitoring the pat...
• Measuring Beliefs Under Ambiguity AI翻译
  作者：Abdellaoui, Mohammed; Bleichrodt, Han; Kemel, Emmanuel; l'Haridon, Olivier
  作者单位：Centre National de la Recherche Scientifique (CNRS); Hautes Etudes Commerciales (HEC) Paris; Erasmus University Rotterdam; Erasmus University Rotterdam - Excl Erasmus MC; Australian National University; Centre National de la Recherche Scientifique (CNRS); CNRS - Institute for Humanities & Social Sciences (INSHS); Universite de Rennes
  摘要：This paper presents a simple method to measure the beliefs of a decision-maker with nonneutral ambiguity attitudes. Our method requires three simple choices, is incentive compatible, and allows for risk aversion and deviations from expected utility, including probability weighting and ambiguity aversion. An experiment using two natural sources of uncertainty (the temperature in Rotterdam and in New York City) shows that the model's estimated beliefs are well calibrated, sensitive to the source...
• Fast Algorithms for Rank-1 Bimatrix Games AI翻译
  作者：Adsul, Bharat; Garg, Jugal; Mehta, Ruta; Sohoni, Milind; von Stengel, Bernhard
  作者单位：Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Bombay; University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign; University of London; London School Economics & Political Science
  摘要：The rank of a bimatrix game is the matrix rank of the sum of the two payoff matrices. This paper comprehensively analyzes games of rank one and shows the following: (1) For a game of rank r, the set of its Nash equilibria is the intersection of a generically one-dimensional set of equilibria of parameterized games of rank r - 1 with a hyperplane. (2) One equilibrium of a rank-1 game can be found in polynomial time. (3) All equilibria of a rank-1 game can be found by following a piecewise linea...
• Bayesian Decision Making in Groups is Hard AI翻译
  作者：Hazla, Jan; Jadbabaie, Ali; Mossel, Elchanan; Rahimian, M. Amin
  作者单位：Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT); Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
  摘要：We study the computations that Bayesian agents undertake when exchanging opinions over a network. The agents act repeatedly on their private information and take myopic actions that maximize their expected utility according to a fully rational posterior belief. We show that such computations are NP-hard for two natural utility functions: one with binary actions and another where agents reveal their posterior beliefs. In fact, we show that distinguishing between posteriors that are concentrated...
• Matching While Learning AI翻译
  作者：Johari, Ramesh; Kamble, Vijay; Kanoria, Yash
  作者单位：Stanford University; University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; Columbia University
  摘要：We consider the problem faced by a service platform that needs to match limited supply with demand while learning the attributes of new users to match them better in the future. We introduce a benchmark model with heterogeneous workers (demand) and a limited supply of jobs that arrive over time. Job types are known to the platform, but worker types are unknown and must be learned by observing match outcomes. Workers depart after performing a certain number of jobs. The expected payoff from a m...
• Dual Moments and Risk Attitudes AI翻译
  作者：Eeckhoudt, Louis R.; Laeven, Roger J. A.
  作者单位：University of Amsterdam; Tilburg University
  摘要：In decision under risk, the primal moments of mean and variance play a central role to define the local index of absolute risk aversion. In this paper, we show that in the canonical nonexpected utility models provided by the dual theory and rank-dependent utility, dual moments have to be used instead of, or on par with, their primal counterparts to obtain an equivalent index of absolute risk aversion.
• Performance of the Smallest-Variance-First Rule in Appointment Sequencing AI翻译
  作者：de Kemp, A. Madelon; Mandjes, Michel; Olver, Neil
  作者单位：University of Amsterdam; University of London; London School Economics & Political Science
  摘要：A classic problem in appointment scheduling with applications in healthcare concerns the determination of the patients' arrival times that minimize a cost function that is a weighted sum of mean waiting times and mean idle times. One aspect of this problem is the sequencing problem, which focuses on ordering the patients. We assess the performance of the smallest-variance-first (SVF) rule, which sequences patients in order of increasing variance of their service durations. Although it is known...