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作者：Zhang, Yu; Zhang, Zhenzhen; Lim, Andrew; Sim, Melvyn
作者单位：Southwestern University of Finance & Economics - China; Tongji University; National University of Singapore; National University of Singapore
摘要：Optimal routing solutions based on deterministic models usually fail to deliver promised on-time services in an uncertain real world, which can lead to the loss of customers and revenue. We study a vehicle routing problem with time windows (VRPTW) toward the end of mitigating the risk of late customer arrivals as much as possible when travel times are based on empirical distributions. To prevent overfitting, we propose a distributionally robust optimization model that uses a Wasserstein distan...
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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...
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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...
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作者：Baggio, Andrea; Carvalho, Margarida; Lodi, Andrea; Tramontani, Andrea
作者单位：Universite de Montreal; Universite de Montreal; Universite de Montreal; Polytechnique Montreal
摘要：In recent years, a lot of effort has been dedicated to develop strategies to defend networks against possible cascade failures or malicious viral attacks. On the one hand, network safety is investigated from a preventive perspective. On the other hand, blocking models have been proposed for scenarios in which the attack has already taken place causing a harmful spreading throughout the network. In this work, we combine these two perspectives. More precisely, following the framework defender-at...
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作者：Broek, Michiel A. J. Uit Het; Schrotenboer, Albert H.; Jargalsaikhan, Bolor; Roodbergen, Kees Jan; Coelho, Leandro C.
作者单位：University of Groningen; Laval University; Laval University
摘要：We present a generic branch-and-cut framework for solving routing problems with multiple depots and asymmetric cost structures, which determines a set of cost-minimizing (capacitated) vehicle tours that fulfill a set of customer demands. The backbone of the framework is a series of valid inequalities with corresponding separation algorithms that exploit the asymmetric cost structure in directed graphs. We derive three new classes of so-called D-k inequalities that eliminate subtours, enforce t...
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作者：Deo, Anand; Juneja, Sandeep
作者单位：Tata Institute of Fundamental Research (TIFR)
摘要：We consider discrete default intensity-based and logit-type reduced-form models for conditional default probabilities for corporate loans where we develop simple closed-form approximations to the maximum likelihood estimator (MLE) when the underlying covariates follow a stationary Gaussian process. In a practical asymptotic regime where the default probabilities are small, say less than 3% annually, and the number of firms and the time period of data available are reasonably large, we rigorous...
