2025

最新文章

• Asymptotically Optimal Clearing Control of Backlogs in Multiclass Processing Systems AI翻译
  作者：Yu, Lun; Iravani, Seyed; Perry, Ohad
  作者单位：The Chinese University of Hong Kong, Shenzhen; Northwestern University; Southern Methodist University
  摘要：We consider a dynamic scheduling problem for a processing system facing the problem of optimally clearing a large backlog of unsatisfied demand from several classes of customers (or jobs). We formulate the problem as a multiclass queueing model with a large initial queue and arrival rates that approximately equal the system's processing capacity. The goal is to find a scheduling policy that minimizes a holding -and -abandonment cost during the transient period in which the system is considered...
• Technical Note-On the Convergence Rate of Stochastic Approximation for Gradient-Based Stochastic Optimization AI翻译
  作者：Hu, Jiaqiao; Fu, Michael C.
  作者单位：State University of New York (SUNY) System; Stony Brook University; University System of Maryland; University of Maryland College Park; University System of Maryland; University of Maryland College Park
  摘要：We consider stochastic optimization via gradient -based search. Under a stochastic approximation framework, we apply a recently developed convergence rate analysis to provide a new finite -time error bound for a class of problems with convex differentiable structures. For noisy black -box functions, our main result allows us to derive finite -time bounds in the setting where the gradients are estimated via finite -difference estimators, including those based on randomized directions such as th...
• Stochastic Localization Methods for Convex Discrete Optimization via Simulation AI翻译
  作者：Zhang, Haixiang; Zheng, Zeyu; Lavaei, Javad
  作者单位：University of California System; University of California Berkeley; University of California System; University of California Berkeley
  摘要：We develop and analyze a set of new sequential simulation-optimization algorithms for large-scale multidimensional discrete optimization via simulation problems with a convexity structure. The large-scale notion refers to that the discrete decision variable has a large number of values from which to choose on each dimension of the decision variable. The proposed algorithms are targeted to identify a solution that is close to the optimal solution given any precision level with any given probabi...
• Achieving Efficiency in Black-Box Simulation of Distribution Tails with Self-Structuring Importance Samplers AI翻译
  作者：Deo, Anand; Murthy, Karthyek
  作者单位：Indian Institute of Management (IIM System); Indian Institute of Management Bangalore; Singapore University of Technology & Design
  摘要：This paper presents a novel importance sampling (IS) scheme for estimating distribution tails of performance measures modeled with a rich set of tools, such as linear programs, integer linear programs, piecewise linear/quadratic objectives, feature maps specified with deep neural networks, etc. The conventional approach of explicitly identifying efficient changes of measure suffers from feasibility and scalability concerns beyond highly stylized models because of their need to be tailored intr...
• Dynamic Portfolio Allocation Under Market Incompleteness and Wealth Effects AI翻译
  作者：Shen, Yiwen; Li, Chenxu; Scaillet, Olivier; Jiang, Yueting
  作者单位：Hong Kong University of Science & Technology; Peking University; University of Geneva; University of Geneva; Chinese University of Hong Kong; University of Hong Kong
  摘要：This paper develops a novel decomposition of optimal dynamic portfolio choice under flexible incomplete-market models and the wealth-dependent hyperbolic absolute risk aversion (HARA) utility. The decomposition reveals the fundamental impacts of market incompleteness and wealth effect in portfolio allocation. With hedgeable interest rate risk, we show that the optimal portfolio under HARA utility can be decomposed into a pure constant relative risk aversion optimal portfolio and a financing bo...
• Optimal Trading with Speed-Dependent Transaction Cost Rates: A Flexible Framework AI翻译
  作者：Liu, Hong; Qian, Shuaijie; Xu, Jing
  作者单位：Washington University (WUSTL); Hong Kong University of Science & Technology; Renmin University of China
  摘要：The effective transaction cost rate (TCR) incurred by a large trade often depends on the execution speed. We propose a continuous-time workhorse model to study optimal trading strategies with speed-dependent TCRs. The TCR function is flexible enough for approximating general TCR functions of trading speeds. Applying our framework to order execution problems, we theoretically characterize the structure of the optimal trading strategy and numerically analyze it extensively after calibration. Whe...
• On the Almost Threshold Policy for Multisourcing Under Uncertain Supplies AI翻译
  作者：Federgruen, Awi; Feng, Qi; Shanthikumar, George
  作者单位：Columbia University; Purdue University System; Purdue University
  摘要：With extended supply chains and increased global sourcing, the uncertainty in supply streams has become a major consideration in formulating procurement strategies. Many studies in the existing literature characterize the optimal procurement policies under specific assumptions of the supply and demand distributions. In several special cases, a threshold policy or an almost threshold policy is shown to be optimal. A recent study by Feng and Shathikumar [Feng Q, Shanthikumar JG (2018) Supply and...
• Improving the Security of United States Elections with Robust Optimization AI翻译
  作者：Crimmins, Braden L.; Halderman, J. Alex; Sturt, Bradley
  作者单位：University of Michigan System; University of Michigan; University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital
  摘要：For more than a century, election officials across the United States have inspected voting machines before elections using a procedure called logic and accuracy testing (LAT). This procedure consists of election officials casting a test deck of ballots into each voting machine and confirming the machine produces the expected vote total for each candidate. We bring a scientific perspective to LAT by introducing the first formal approach to designing test decks with rigorous security guarantees....
• A Reciprocity Between Tree Ensemble Optimization and Multilinear Optimization AI翻译
  作者：Kim, Jongeun; Richard, Jean-Philippe P.; Tawarmalani, Mohit
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; Purdue University System; Purdue University
  摘要：In this paper, we establish a low-degree polynomially-sized reduction between tree ensemble optimization and optimization of multilinear functions over a Cartesian product of simplices. We use this insight to derive new formulations for tree ensemble optimization problems and to obtain new convex hull results for multilinear polytopes. A computational experiment on multicommodity transportation problems with costs modeled using tree ensembles shows the practical advantage of our formulation re...
• Linear Classifiers Under Infinite Imbalance AI翻译
  作者：Glasserman, Paul; Li, Mike
  作者单位：Columbia University
  摘要：We study the behavior of linear discriminant functions for binary classification in the infinite-imbalance limit, where the sample size of one class grows without bound while the sample size of the other remains fixed. The coefficients of the classifier minimize an empirical loss specified through a weight function. We show that for a broad class of weight functions, the intercept diverges but the rest of the coefficient vector has a finite almost sure limit under infinite imbalance, extending...