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作者：Maragno, Donato; Wiberg, Holly; Bertsimas, Dimitris; Birbil, S. . Ilker; den Hertog, Dick; Fajemisin, Adejuyigbe O.
作者单位：University of Amsterdam; Carnegie Mellon University; Massachusetts Institute of Technology (MIT)
摘要：We establish a broad methodological foundation for mixed-integer optimization with learned constraints. We propose an end-to-end pipeline for data-driven decision making in which constraints and objectives are directly learned from data using machine learning, and the trained models are embedded in an optimization formulation. We exploit the mixed-integer optimization representability of many machine learning methods, including linear models, decision trees, ensembles, and multilayer perceptro...
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作者：Ye, Heng-Qing
作者单位：Hong Kong Polytechnic University
摘要：We study a system with heterogeneous parallel servers, each with an infinite waiting room. Upon arrival, a job is routed to the queue of one of the servers, possibly depending on the dynamic state information such as the real-time queue lengths, the arrival, and service history of jobs. The objective is to find the routing policy that best uses the available state information to minimize the expected stationary queue length. In this paper, we establish the diffusion limit for the round-robin p...
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作者：Meng, Xiaochun; Taylor, James W.; Taieb, Souhaib Ben; Li, Siran
作者单位：University of Sussex; University of Oxford; University of Mons; Shanghai Jiao Tong University; Shanghai Jiao Tong University
摘要：Forecasts of multivariate probability distributions are required for a variety of applications. Scoring rules enable the evaluation of forecast accuracy and comparison between forecasting methods. We propose a theoretical framework for scoring rules for multivariate distributions that encompasses the existing quadratic score and multivariate continuous ranked probability score. We demonstrate how this framework can be used to generate new scoring rules. In some multivariate contexts, it is a f...
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作者：Eckstein, Jonathan; Watson, Jean-Paul; Woodruff, David L.
作者单位：Rutgers University System; Rutgers University New Brunswick; Rutgers University Newark; United States Department of Energy (DOE); Lawrence Livermore National Laboratory; University of California System; University of California Davis
摘要：We propose a decomposition algorithm for multistage stochastic programming that resembles the progressive hedging method of Rockafellar and Wets but is provably capable of several forms of asynchronous operation. We derive the method from a class of projective operator splitting methods fairly recently proposed by Combettes and Eckstein, significantly expanding the known applications of those methods. Our derivation assures convergence for convex problems whose feasible set is compact, subject...
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作者：Lu, Haihao; Yang, Jinwen
作者单位：Massachusetts Institute of Technology (MIT); University of Chicago
摘要：In this paper, we provide an affirmative answer to the long-standing question: Are GPUs useful in solving linear programming? We present cuPDLP.jl, a GPU implementation of restarted primal-dual hybrid gradient for solving linear programming (LP). We show that this prototype implementation in Julia has comparable numerical performance on standard LP benchmark sets to Gurobi, a highly optimized implementation of the simplex and interiorpoint methods. This demonstrates the power of using GPUs in ...
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作者：Chen, Li; Sim, Melvyn; Zhang, Xun; Zhao, Long; Zhou, Minglong
作者单位：University of Sydney; National University of Singapore; Chinese Academy of Sciences; University of Science & Technology of China, CAS; Fudan University
摘要：We propose a new robust actionable prescriptive analytics framework that leverages past data and side information to minimize a risk-based objective function under distributional ambiguity. Our framework aims to find a policy that directly transforms the side information into implementable decisions. Specifically, we focus on developing actionable response policies that offer the benefits of interpretability and implementability. To address the potential issue of overfitting to empirical data,...
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作者：Jiang, Zhaohui (Zoey); Li, Jun
作者单位：Carnegie Mellon University; University of Michigan System; University of Michigan
摘要：Accurate operational decisions require precise knowledge of the causal effects of such decisions on outcomes, a task that becomes increasingly complex in dynamic business environments. We propose an idea of instrumenting while experimenting, whereby researchers can create their own instruments by injecting small, random variations directly into the decision-making process and then use such variations to obtain causal estimates of the impact of varying business decisions at scale without disrup...
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作者：Zubeldia, Martin; Jhunjhunwala, Prakirt R.; Maguluri, Siva Theja
作者单位：University of Minnesota System; University of Minnesota Twin Cities; Columbia University; University System of Georgia; Georgia Institute of Technology
摘要：Inspired by quantum switches, we consider a discrete-time multiway matching system with two classes of arrivals: requests for entangled pair of qubits between two nodes and qubits from each node that can be used to serve the requests. An important feature of this model is that qubits decohere and so abandon over time. In contrast to classical server-based queueing models, the combination of queueing, server-less multiway matching, and (potentially correlated) abandonments make the analysis a c...
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作者：Scully, Ziv; van Kreveld, Lucas
作者单位：Cornell University; Eindhoven University of Technology
摘要：We consider scheduling in the M/G/1 queue with unknown job sizes. It is known that the Gittins policy minimizes mean response time in this setting. However, the behavior of the tail of response time under Gittins is poorly understood, even in the largeresponse -time limit. Characterizing Gittins's asymptotic tail behavior is important because if Gittins has optimal tail asymptotics, then it simultaneously provides optimal mean response time and good tail performance. In this work, we give the ...
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作者：Buke, Burak; dos Reis, Goncalo; Platonov, Vadim
作者单位：University of Edinburgh; Universidade Nova de Lisboa; Universidade de Lisboa
摘要：In most service systems, the servers are humans who desire to experience a certain level of idleness. In call centers, this manifests itself as call-avoidance behavior when servers strategically adjust their service rate to strike a balance between the idleness they receive and effort to work harder. Moreover, being human, each server values this tradeoff differently and has different capabilities. We develop a novel framework, relying on measure-valued processes and mean-field game theory, to...
