Operations Research

最新文章

• Partial Recovery in the Graph Alignment Problem AI翻译
  作者：Hall, Georgina; Massoulie, Laurent
  作者单位：INSEAD Business School; Inria
  摘要：In this paper, we consider the graph alignment problem, which is the problem of recovering, given two graphs, a one-to-one mapping between nodes that maximizes edge overlap. This problem can be viewed as a noisy version of the well-known graph isomorphism problem and appears in many applications, including social network deanonymization and cellular biology. Our focus here is on partial recovery; that is, we look for a one-to-one mapping that is correct on a fraction of the nodes of the graph ...
• The Anchor-Robust Project Scheduling Problem AI翻译
  作者：Bendotti, Pascale; Chretienne, Philippe; Fouilhoux, Pierre; Pass-Lanneau, Adele
  作者单位：Electricite de France (EDF); Centre National de la Recherche Scientifique (CNRS); Sorbonne Universite
  摘要：In project scheduling with uncertain processing times, the decision maker often needs to compute a baseline schedule in advance while guaranteeing that some jobs will not be rescheduled later. Standard robust approaches either produce a schedule with a very large makespan or offer no guarantee on starting times of the jobs. The concept of anchor-robustness is introduced as a middle ground between these approaches. A subset of jobs is said to be anchored if the starting times of its jobs in the...
• Every Choice Function Is Pro-Con Rationalizable AI翻译
  作者：Dogan, Serhat; Yildiz, Kemal
  作者单位：Ihsan Dogramaci Bilkent University
  摘要：We consider an agent who is endowed with two sets of orderings: pro-and con orderings. For each choice set, if an alternative is the top-ranked by a pro-ordering (con-ordering), then this is a pro (con) for choosing that alternative. The alternative with more pros than cons is chosen from each choice set. Each ordering may have a weight reflecting its salience. In this case, the probability that an alternative is chosen equals the difference between the total weights of its pros and cons. We s...
• Air Passenger Preferences: An International Comparison Affects Boarding Theory AI翻译
  作者：Bachmat, Eitan; Erland, Sveinung; Jaehn, Florian; Neumann, Simone
  作者单位：Ben-Gurion University of the Negev; Simons Foundation; Western Norway University of Applied Sciences; Helmut Schmidt University
  摘要：Managerial optimization challenges in service industries often entail the need to ensure customer satisfaction. For example, in airplane boarding, the boarding time should be minimized, but to ensure customer satisfaction, the process must not be too stressful for passengers. However, many authors assume that total boarding time minimization and customer satisfaction are complementary goals, even though there is little empirical knowledge on the topic. We challenge this assumption and contend ...
• Revenue Management Under a Mixture of Independent Demand and Multinomial Logit Models AI翻译
  作者：Cao, Yufeng; Rusmevichientong, Paat; Topaloglu, Huseyin
  作者单位：Shanghai Jiao Tong University; University of Southern California
  摘要：We consider assortment optimization problems when customers choose under a mixture of independent demand and multinomial logit models. In the assortment optimization setting, each product has a fixed revenue associatedwith it. The customers choose among the products according to our mixture choice model. The goal is to find an assortment that maximizes the expected revenue from a customer. We show that we can find the optimal assortment by solving a linear program. We establish that the optima...
• Subset Selection with Shrinkage: Sparse Linear Modeling When the SNR Is Low AI翻译
  作者：Mazumder, Rahul; Radchenko, Peter; Dedieuc, Antoine
  作者单位：Massachusetts Institute of Technology (MIT); University of Sydney
  摘要：We study a seemingly unexpected and relatively less understood overfitting aspect of a fundamental tool in sparse linear modeling-best subset selection-which minimizes the residual sum of squares subject to a constraint on the number of nonzero coefficients. Whereas the best subset selection procedure is often perceived as the gold standard in sparse learning when the signal-to-noise ratio (SNR) is high, its predictive performance deteriorates when the SNR is low. In particular, it is outperfo...
• Simulation-Based Prediction AI翻译
  作者：Lim, Eunji; Glynn, Peter W.
  作者单位：Adelphi University; Stanford University
  摘要：This paper is concerned with the use of simulation in computing predictors in settings in which real-world observations are collected. A major challenge is that the state description underlying the simulation will typically include information that is not observed in the real system. This makes it challenging to initialize simulations that are aligned with the most recent observation collected in the real-world system, especially when the simulation does not visit the most recently observed va...
• Optimizing Risk-Balancing Return Under Discrete Choice Models AI翻译
  作者：Li, Hongmin; Webster, Scott
  作者单位：Arizona State University; Arizona State University-Tempe
  摘要：We examine a firm's pricing decision when managing a broad product line with the goal of optimally balancing the expected return on product investment with the revenue or profit risk associated with uncertain customer choices. We consider the multinomial logit (MNL) model and the mean-variance objective function and illustrate how the level of risk tolerance influences the firm's optimal markups. We show that the solution approach and results generalize to the nested logit (NL) choice model an...
• Dynamic Mechanism Design with Capacity Constraint AI翻译
  作者：He, Wei
  作者单位：Chinese University of Hong Kong
  摘要：We study a project assignment problem, where a principal needs to assign multiple projects to an agent. The agent is privately informed about the cost, which could be high or low. The agent's type evolves stochastically over time. We fully characterize the optimal mechanism via a sequence of deadlines and show that the presence of the capacity constraint reduces the principal's payoff and delays the assignment of projects. In particular, as the number of projects increases, the limit optimal c...
• Stall Economy: The Value of Mobility in Retail on Wheels AI翻译
  作者：Cao, Junyu; Qi, Wei
  作者单位：University of Texas System; University of Texas Austin; Tsinghua University
  摘要：Urban open space emerges as a new territory to embrace retail innovations. Selling products in public spaces with wheeled stalls can potentially become ubiquitous in our future cities. Transition into such a stall economy paradigm is being spurred by the rapidly advancing self-driving technologies. Motivated by this transformation, this paper provides models, theory, and insights of spatial queueing systems, in which one server moves around to meet mobile customers/machines and in which the la...