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The Influence of Digital Adoption, Absorptive Capacity and Risk Management Implementation on Organizational Resilience: An Empirical Study in The Indonesian Banking Industry 2

The Influence of Digital Adoption, Absorptive Capacity and R...

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Tjahyono, Boy Prabowo, Harjanto Alamsjah, Firdaus Hamsal, Mohammad Binus Graduate Program Binus Business School Research in Management Jakarta Indonesia Binus Graduate Program Binus Business School Industrial Engineering Jakarta Indonesia

ISBN: (纸本)9798350360523

One of the primary difficulties of Indonesia's banking sector is to ensure that it continues to develop in business, is robust, and can foresee new risks while enhancing governance, risk, and compliance. This study will determine the effect of risk management implementation, absorptive capacity, and digital adoption on organizational resilience. The survey method is being used as a research method, with targeted respondents from senior executives, including C-suites, senior vice presidents, and vice presidents. The results show that digital adoption and absorptive capacity impact risk management implementation and organizational resilience despite the limited research available in the Indonesian banking sector. The study will contribute to understanding how enterprise resilience is affected by risk management. This research has presented an opportunity for both banking management and policymakers to formulate strategies aimed at bolstering organizational resilience within the banking sector. These strategies could aid in navigating unforeseen and disruptive business environments. Furthermore, this study stands to expand the application of concepts such as organizational resilience and dynamic capacity theory, particularly within the banking industry of developing nations. © 2024 IEEE.

关键词： Risk management

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Co-optimization of Short- and Long-term Decisions for the Transmission Grid’s Resilience to Flooding

arXiv

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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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Optimal Location and Sizing of Energy Storage Systems to Enhance Power Grid Resilience

Optimal Location and Sizing of Energy Storage Systems to Enh...

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IISE Annual Conference and Expo 2022

作者： Bilir, Barış Kutanoglu, Erhan Hasenbein, John J. Operations Research and Industrial Engineering Program The University of Texas at Austin AustinTX United States

ISBN: (纸本)9781713858072

Extreme weather events result in devastating damages in the U.S. These low probability, high impact events can cause widespread power outages and cost billions of dollars to society. Scientists predict that such events will be more frequent and more intense, and last longer with climate change. Therefore, it is important to explicitly incorporate resiliency while making decisions regarding the future design of the power grid as a way of adapting the grid to the increasing extreme weather risks. Considering the increasing penetration of renewable energy sources and decreasing prices of energy storage systems, an example of such a design consideration is integration of energy storage systems. In this paper, we propose a scenario-based two-stage stochastic programming model to determine optimal location and sizing of energy storage systems to enhance power grid resilience. The model adapts the power grid using scenarios based on winter storms and their impacts. Computational experiments quantify the resilience benefits of energy storage systems under a variety of conditions using the synthetic Texas grid as a case study. © 2022 IISE Annual Conference and Expo 2022. All rights reserved.

关键词： Stochastic systems

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Comparison of Linear Power Flow Approximations in the Context of Winter Storm Planning

Comparison of Linear Power Flow Approximations in the Contex...

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IISE Annual Conference and Expo 2022

作者： Austgen, Brent Kutanoglu, Erhan Hasenbein, John J. Operations Research and Industrial Engineering Program The University of Texas at Austin AustinTX United States

ISBN: (纸本)9781713858072

The resilience of the Texas power grid has been tested by winter storms and the attendant cold on multiple occasions. Notable events include the United States cold wave of December 1989, the Groundhog Day Blizzard of 2011, and most recently Winter Storm Uri of 2021. With these events in mind, we propose a two-stage stochastic programming model for informing winterization investment decisions for generators. First-stage decisions pertain to investments, and second-stage decisions are power generation and load shed in an optimal power flow problem. The objective is to minimize the expected load shed across a set of plausible winter storm outage scenarios, each featuring multiple simultaneous generator outages and derates. We apply the model to a synthetic power grid instance and use scenarios developed from Winter Storm Uri generator outage and derate data. We assess and compare the optimal first-stage decisions that result from using different approximations of AC power flow to comprise the second-stage problem. © 2022 IISE Annual Conference and Expo 2022. All rights reserved.

关键词： Stochastic programming

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Scenario-based Optimization Models for Power Grid Resilience to Extreme Flooding Events

arXiv

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arXiv 2023年

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

We propose two scenario-based optimization models for power grid resilience decision making that integrate output from a hydrology model with a power flow model. The models are used to identify an optimal substation hardening strategy against potential flooding from storms for a given investment budget, which if implemented enhances the resilience of the power grid, minimizing the power demand that is shed. The same models can alternatively be used to determine the optimal budget that should be allocated for substation hardening when long-term forecasts of storm frequency and impact (specifically restoration times) are available. The two optimization models differ in terms of capturing risk attitude: one minimizes the average load shed for given scenario probabilities and the other minimizes the worst-case load shed without needing scenario probabilities. To demonstrate the efficacy of the proposed models, we further develop a case study for the Texas Gulf Coast using storm surge maps developed by the National Oceanic and Atmospheric Administration and a synthetic power grid for the state of Texas developed as part of an ARPA-E project. For a reasonable choice of parameters, we show that a scenario-based representation of uncertainty can offer a significant improvement in minimizing load shed as compared to using point estimates or average flood values. We further show that when the available investment budget is relatively high, solutions that minimize the worst-case load shed can offer several advantages as compared to solutions obtained from minimizing the average load shed. Lastly, we show that even for relatively low values of load loss and short post-hurricane power restoration times, it is optimal to make significant investments in substation hardening to deal with the storm surge considered in the NOAA flood scenarios. © 2023, CC BY.

关键词： Hurricanes

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Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm

arXiv

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arXiv 2024年

作者： Berahas, Albert S. Bollapragada, Raghu Dong, Wanping Department of Industrial and Operations Engineering University of Michigan United States Operations Research and Industrial Engineering Program University of Texas at Austin United States

In this paper, we propose algorithms that exploit negative curvature for solving noisy nonlinear nonconvex unconstrained optimization problems. We consider both deterministic and stochastic inexact settings, and develop two-step algorithms that combine directions of negative curvature and descent directions to update the iterates. Under reasonable assumptions, we prove second-order convergence results and derive complexity guarantees for both settings. To tackle large-scale problems, we develop a practical variant that utilizes the conjugate gradient method with negative curvature detection and early stopping to compute a step, a simple adaptive step size scheme, and a strategy for selecting the sample sizes of the gradient and Hessian approximations as the optimization progresses. Numerical results on two machine learning problems showcase the efficacy and efficiency of the practical method. Copyright © 2024, The Authors. All rights reserved.

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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Enhancing Safety Measures in a Steel Manufacturing Facility;Factory X Case Study

Enhancing Safety Measures in a Steel Manufacturing Facility;...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Ali, Mariam Kassem, Sally S. Elatriby, Sherif A. Nile University Industrial Engineering Program Smart Engineering Systems Research Center Giza12613 Egypt Cairo Univesityt Faculty of Computers and Artificial Intelligence Operations Research and Decision Support Department Giza12613 Egypt University Helwan Faculty of Engineering Helwan Cairo11792 Egypt

ISBN: (纸本)9798350369106

Productivity and safety of the workers have been issues in most manufacturing facilities in Egypt and all over the world, as the main aim of any manufacturing facility is to increase profit and limit costs as much as possible. Through analysis and simulation, this paper aims to create a safe workplace for the worker;risk assessment and Failure Mode and Effect Analysis (FMEA) and the basics of the international standards ISO 31000 and ISO 45001 have been conducted to evaluate different hazards and potential risks. Moreover, lean tools such as 6S and Visual Management are proposed solutions to enhance workplace safety and decrease the possibility or severity of potential risks. Therefore, a new workplace design, an example of a high-level hazard in industry in Egypt's local market, has been established for the steel manufacturing facility under consideration using Sketch Up. The results of the proposed solutions, such as new frameworks, worker safety training, equipment replacements, and applying lean tools, have shown a practically acceptable percentage of safety improvements and a decreasing risk priority number (RPN). The percentage decrease for (RPN) ranges between 31.43% to 90.47% for different potential risks. © 2024 IEEE.

关键词： Agile manufacturing systems

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Function Based Damage Resistance Modeling for Multi-Phase CPS System Reliability 29

Function Based Damage Resistance Modeling for Multi-Phase CP...

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29th ISSAT International Conference on Reliability and Quality in Design, RQD 2024

作者： Lin, Huizhong Zhu, Mengmeng Department of Textile Engineering Chemistry and Science North Carolina State University RaleighNC United States Operations Research Graduate Program North Carolina State University RaleighNC United States

ISBN: (纸本)9798986576138

The damage resistance cyber-physical system (CPS) has gained growing attention in research communities. Recent studies typically describe a system's resistance to shock damage using a constant factor ranging from 0 to 1, which may not accurately represent the system's true resistance due to operational intricacies. This paper introduces a resistance function employing a logarithmic form to illustrate the system's dynamic resistance to shock damage. Initially, we present the process of modeling this resistance function and examine its statistical characteristics. Subsequently, we expand upon the three types of non-fatal shocks outlined in previous studies, applying them to a multi-phase context and exploring the impact of each type of non-fatal shock across the system's three degradation phases. Using the proposed resistance function, we formulate an explicit solution for a damage resistance multiphase system reliability model. Finally, numerical examples are provided to show that the reliability model developed offers a good depiction of the system's reliability characteristics. © Conference Proceedings of the 29th ISSAT International Conference on Reliability and Quality in Design, RQD 2024.

关键词： Shock problems

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