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arXiv 2025年

作者： Shukla, Ashutosh Kutanoglu, Erhan Hasenbein, John Graduate Program in Operations Research and Industrial Engineering The University of Texas at Austin AustinTX United States

We present and analyze a three-stage stochastic optimization model that integrates output from a geoscience-based flood model with a power flow model for transmission grid resilience planning against flooding. The proposed model coordinates the decisions made across multiple stages of resilience planning and recommends an optimal allocation of the overall resilience investment budget across short- and long-term measures. While doing so, the model balances the cost of investment in both short- and long-term measures against the cost of load shed that results from unmitigated flooding forcing grid components go out-of-service. We also present a case study for the Texas Gulf Coast region to demonstrate how the proposed model can provide insights into various grid resilience questions. Specifically, we demonstrate that for a comprehensive yet reasonable range of economic values assigned to load loss, we should make significant investments in the permanent hardening of substations such that we achieve near-zero load shed. We also show that not accounting for short-term measures while making decisions about long-term measures can lead to significant overspending. Furthermore, we demonstrate that a technological development enabling to protect substations on short notice before imminent hurricanes could vastly influence and reduce the total investment budget that would otherwise be allocated for more expensive substation hardening. Lastly, we also show that for a wide range of values associated with the cost of mitigative long-term measures, the proportion allocated to such measures dominates the overall resilience spending. Copyright © 2025, The Authors. All rights reserved.

关键词： Stochastic systems

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A Stochastic Gradient Tracking Algorithm for Decentralized Optimization With Inexact Communication

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IEEE Transactions on Automatic Control 2025年

作者： Shah, Suhail M. Bollapragada, Raghu University of Texas at Austin Operations Research and Industrial Engineering Program TX78705 United States

Decentralized optimization is typically studied under the assumption of noise-free transmission. However, real-world scenarios often involve the presence of noise due to factors such as additive white Gaussian noise channels or probabilistic quantization of transmitted data. These sources of noise have the potential to degrade the performance of decentralized optimization algorithms if not effectively addressed. In this paper, we focus on the noisy communication setting and propose an algorithm that bridges the performance gap caused by communication noise while also mitigating other challenges like data heterogeneity. We establish theoretical results of the proposed algorithm that quantify the effect of communication noise and gradient noise on the performance of the algorithm. Notably, our algorithm achieves the optimal convergence rate for minimizing strongly convex, smooth functions in the context of inexact communication and stochastic gradients. Finally, we illustrate the superior performance of the proposed algorithm compared to its state-of-the-art counterparts on machine learning problems using MNIST and CIFAR-10 datasets. © 2025 IEEE.

关键词： Optimization algorithms

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Joint optimization of logistics operations and reliability-based replacement policies in a geographically distributed service parts logistic system

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CIRP Annals 2025年

作者： Wang, Po-Han Djurdjanovic, Dragan Graduate Program on Operations Research and Industrial Engineering The University of Texas at Austin AustinTX United States Walker Department of Mechanical Engineering The University of Texas at Austin AustinTX United States

A joint location-inventory-maintenance model is proposed for a geographically distributed Service Parts Logistics problem. The model uses a reliability-based replacement strategy and is formulated as a quadratic Mixed Integer Linear program which jointly optimizes logistic and preventive part replacement decisions. The proposed solution method employs piecewise linearization to provide a level of tractability and scalability to the method. The newly proposed joint location-inventory-maintenance model is evaluated and benchmarked against traditional local optimum-based replacement approaches. It consistently outperformed the benchmark models, with the efficiency of cost effect improvements determined by the relative prevalence of logistics factors versus asset management costs. © 2025

关键词： Piecewise linear techniques

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Deep Learning-Based Residual Useful Lifetime Prediction for Assets With Uncertain Failure Modes

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Journal of Computing and Information Science in engineering 2025年第4期25卷 041002页

作者： Su, Yuqi Fang, Xiaolei Operations Research Graduate Program North Carolina State University 915 Partners Way Raleigh NC 27607 Edward P. Fitts Department of Industrial and Systems Engineering North Carolina State University 915 Partners Way Raleigh NC 27607

industrial prognostics focuses on utilizing degradation signals to forecast and continually update the residual useful life of complex engineering systems. However, existing prognostic models for systems with multiple failure modes face several challenges in real-world applications, including overlapping degradation signals from multiple components, the presence of unlabeled historical data, and the similarity of signals across different failure modes. To tackle these issues, this research introduces two prognostic models that integrate the mixture (log)-location-scale distribution with deep learning. This integration facilitates the modeling of overlapping degradation signals, eliminates the need for explicit failure mode identification, and utilizes deep learning to capture complex nonlinear relationships between degradation signals and residual useful lifetimes. Numerical studies validate the superior performance of these proposed models compared to existing methods.

关键词： Failure mechanisms mixture (log)-location-scale distribution Failure Weibull distribution multiple failure modes Signals Service life (Equipment) prognostics data analytics Deep learning machine learning for engineering applications engineering systems and industry applications industrial Internet of things big data and analytics

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Gancqr: Estimating Prediction Intervals for Individual Treatment Effects with Gans 24

Gancqr: Estimating Prediction Intervals for Individual Treat...

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Proceedings of the Winter Simulation Conference

作者： Jiaxing Wang Hong Wan Xi Chen Operations Research Graduate Program North Carolina State University Raleigh NC USA Edward P. Fitts Dept. of Industrial and Systems Eng. North Carolina State University Raleigh NC USA Grado Dept. of Industrial and Systems Eng. Virginia Tech Blacksburg VA USA

ISBN: (纸本)9798331534202

Evaluating individual treatment effects (ITE) is challenging due to the lack of access to counterfactual outcomes, particularly when working with biased data. Recent efforts have focused on leveraging the generative capabilities of models like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) for ITE estimation. However, few approaches effectively address the need for uncertainty quantification in these estimates. In this work, we introduce GANCQR, a GAN-based conformal prediction method that generates prediction intervals for ITE with reliable coverage. Numerical experiments on synthetic and semi-synthetic datasets demonstrate GANCQR's superiority in handling selection bias compared to state-of-the-art methods.

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Conductive RuO₂ binders enhance mechanical stability of macroporous Nb-SnO₂ particles as cathode catalyst supports for high-performance PEFCs

RSC Applied Interfaces

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RSC Applied Interfaces 2025年第3期2卷 795.0-807.0页

作者： Ho, Thi Thanh Nguyen Hirano, Tomoyuki Takano, Aoi Miyasaka, Syu Tanabe, Eishi Maeda, Makoto Septiani, Eka Lutfi Cao, Kiet Le Anh Ogi, Takashi Chemical Engineering Program Graduate School of Advanced Science and Engineering Hiroshima University 1-4-1 Kagamiyama Higashihiroshima Hiroshima 739-8527 Japan Cataler Corporation 7800 Chihama Shizuoka Kakegawa 437-1492 Japan Hiroshima Prefectural Institute of Industrial Science and Technology 3-10-31 Kagamiyama Higashi Hiroshima Hiroshima 739-0046 Japan Natural Science Center for Basic Research and Development Hiroshima University 1-4-1 Kagamiyama Higashihiroshima739-8527 Hiroshima 739-8527 Japan

Niobium-doped tin oxide (NTO) particles with a macroporous structure have been developed as catalyst supports for enhancing the durability and performance of polymer electrolyte fuel cells (PEFCs). This macroporous architecture improves the mass transport properties of the electrode. However, their weak mechanical strength can cause structural collapse, thereby limiting single-cell performance at high current densities. In this study, we employed ruthenium oxide (RuO₂) as a binder to integrate with macroporous NTO particles (denoted as NTO/RuO₂). This approach simultaneously enhanced the electrical conductivity and mechanical strength of the catalyst supports, improving the performance of PEFCs. Incorporating RuO₂ binders effectively stabilized the macroporous structure, and the NTO/RuO₂ particles with 50 wt% RuO₂ loading maintained their structural integrity under high compression pressures of up to 40 MPa. The aggregated NTO/RuO₂ particles containing 50 wt% RuO₂ binder also exhibited higher conductivity than the NTO aggregates without RuO₂ binder, which was attributed to the conductive network formed by RuO₂. Importantly, the membrane electrode assembly (MEA) fabricated with macroporous NTO/RuO₂ particles containing 20 wt% RuO₂ binder achieved a maximum current density of 2.16 A cm⁻² at 60 °C and 100% relative humidity (RH), outperforming the MEA utilizing Carbon Vulcan as the support (2.06 A cm⁻²). Furthermore, the enhanced hydrophilic properties of the RuO₂ binder improved water retention at the catalyst layer/membrane interface, thus promoting membrane hydration and overall cell performance at a high temperature of 80 °C and a low RH of 30%. © 2025 RSC.

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Conformal Tail Risk Control for Large Language Model Alignment

arXiv

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arXiv 2025年

作者： Chen, Catherine Yu-Chi Shen, Jingyan Deng, Zhun Lei, Lihua Institute for Computational and Mathematical Engineering Stanford University United States Department of Industrial Engineering and Operations Research Columbia University United States Department of Computer Science University of North Carolina Chapel Hill United States Graduate School of Business Department of Statistics Stanford University United States

Recent developments in large language models (LLMs) have led to their widespread usage for various tasks. The prevalence of LLMs in society implores the assurance on the reliability of their performance. In particular, risk-sensitive applications demand meticulous attention to unexpectedly poor outcomes, i.e., tail events, for instance, toxic answers, humiliating language, and offensive outputs. Due to the costly nature of acquiring human annotations, general-purpose scoring models have been created to automate the process of quantifying these tail events. This phenomenon introduces potential human-machine misalignment between the respective scoring mechanisms. In this work, we present a lightweight calibration framework for blackbox models that ensures the alignment of humans and machines with provable guarantees. Our framework provides a rigorous approach to controlling any distortion risk measure that is characterized by a weighted average of quantiles of the loss incurred by the LLM with high confidence. The theoretical foundation of our method relies on the connection between conformal risk control and a traditional family of statistics, i.e., L-statistics. To demonstrate the utility of our framework, we conduct comprehensive experiments that address the issue of human-machine misalignment. © 2025, CC BY.

关键词： Risk assessment

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Benchmarking simulation software for use in modeling postal operations

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COMPUTERS & industrial engineering 1997年第3期32卷 607-625页

作者： Bard, JF Graduate Program in Operations Research & Industrial Engineering Department of Mechanical Engineering University of Texas Austin TX 78712-1063USA

This paper reports on the second component of a three phase study undertaken for the Canada Post Corporation (CPC) to evaluate and select a commercial simulation package to be used for operational and long-term planning. The formal evaluation process consisted of a hierarchical screening procedure to identify qualified candidates and the development of a comprehensive benchmark model to test each candidate. Of the 172 simulation packages listed in the Directory of Simulation, only three satisfied each of the CPC's highest priority requirements. Data, mail flows, and processing logic associated with operations at the Hamilton, Ontario plant were used to establish the benchmarks and validate the models. This project represents the first time full-scale models have been constructed in parallel to evaluate graphics-based simulation software. Although several economies of scale were realized, the differences in the three packages meant significant duplication. Nevertheless, the CPC felt that the parallel approach would return benefits in the long run and that it was necessary to arrive at a considered decision. A major aim of this paper is to highlight the methodology used in the analysis and to present the lessons learned from the project. (C) 1997 Elsevier Science Ltd.

关键词： Postal services

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Block scheduling in a multi-hospital setting

Operations Research, Data Analytics and Logistics

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operations research, Data Analytics and Logistics 2025年

作者： Vishrut Rana Candace Arai Yano Alexandra M. Newman Wharton School University of Pennsylvania Philadelphia PA 19104-6340 United States Department of Industrial Engineering and Operations Research and Haas School of Business University of California Berkeley CA 94720 United States Operations Research with Engineering Graduate Program Colorado School of Mines Golden CO 80401 USA

We seek to optimize a multi-week repeating block schedule for operating rooms at multiple hospitals under the same corporate umbrella. Allowing patients to undergo surgical procedures at a broader set of hospitals improves access in general, and to advanced surgical (robotic) technology that may not exist at the nearest hospital to the patient, in particular. In our problem, a block consists of combinations of surgery types that can be performed by one surgeon in the same operating room on one day, and is associated with prospective patients from a specific locale. Blocks must be assigned to a suitable operating room at an allowable hospital. Patients within each block have a designated hospital ward for recovery, and their length-of-stay distributions depend upon their surgery type. Our model includes nursing costs, penalties for surgical-patient census exceeding the target capacity in each hospital ward and assignment of blocks to non-home hospitals; bonuses accrue for scheduling blocks in high-tech operating rooms. We include constraints on patient-to-nurse ratios and surgeon availability, among others. We present a numerical example based on real and realistic data to illustrate the effects of strategic decisions and characteristics of important tradeoffs. In particular, we explore the tradeoff between greater use of high-tech operating rooms, which reduces patient recovery time, complications and readmissions, and higher nursing-related costs. To the best of our knowledge, our model is the first multi-week, multi-hospital block scheduling problem to be presented. The model is quite general and can be adapted to consider an array of other factors.

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Vitrification of hazardous wastes from ship recycling: circular economy solutions for asbestos and synthetic vitreous fibers

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Environmental Science and Pollution research 2025年第13期32卷 8183-8200页

作者： Pereira, Newton Narciso de Castro Bertagnolli, Denise da Silva, Ladário Faria, Eliel Eleutério Junior, José Mauro Moraes de Araujo de Monteiro Barros, Munique Eva Paiva Miranda, Tainara Alves de Oliveira Lima, Eduardo da Silva Almeida, Vitor Duarte Department of Production Engineering School of Industrial Engineering and Metallurgy at Volta Redonda - EEIMVR – Federal Fluminense University UFF Av. dos Trabalhadores 420 – Sala C77 Vila Sta. Cecília RJ Volta Redonda27255-125 Brazil Department of Chemistry Exact Sciences Institute Federal Fluminense University UFF Rua Desembargador Ellis Hermydio Figueira 783 RJ AterradoVolta Redonda27213-145 Brazil Department of Physics Exact Sciences Institute Federal Fluminense University UFF Rua Desembargador Ellis Hermydio Figueira 783 RJ AterradoVolta Redonda27213-145 Brazil Department of Physics Universidade Federal de Roraima Av. Cap. Ene Garcez N. 2413 Paricarana Roraima Boa Vista69310-000 Brazil Departament of Metallurgical Engineering Federal Fluminense University UFF Av. dos Trabalhadores 420 Vila Sta. Cecília RJ Volta Redonda27255-125 Brazil Physics Post-Graduate Program Brazilian Center for Physics Research Rua Doutor Xavier Sigaud 150 Urca RJ Rio de Janeiro22290-180 Brazil Physics Post-Graduate Program Physics Institute Federal Fluminense University UFF Av. Gal. Milton Tavares de Souza S/nº Praia Vermelha Campus RJ Niterói24210-346 Brazil

Ship recycling at the end of its useful life presents significant environmental and health challenges due to the presence of hazardous materials, such as asbestos and synthetic vitreous fibers (SVFs). This study aimed to convert SVFs and asbestos into safe, reusable co-products by incorporating them into a glassy matrix. The materials were melted at 1200 °C for 1 h with utilization of niobium pentoxide (Nb2O5) to lower fusion temperatures. Samples collected from an offshore vessel and platform being recycled in Rio de Janeiro, Brazil, were analyzed using energy-dispersive x-ray spectroscopy (EDS) and scanning electron microscopy (SEM), revealing the presence of SVFs but not asbestos. Seven types of glass were produced, with their non-crystalline, glassy nature confirmed by the presence of an amorphous halo in X-ray diffraction (XRD) and a glass transition observed in differential scanning calorimetry (DSC). These findings demonstrate the potential to transform hazardous waste into value-added products, advancing a circular economy in ship recycling operations. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Asbestos

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