Prescriptive Analytics-based Robust Decision-making Model for Cyber Disaster Risk Reduction (2024)

Ponnoly, J., Puthenveetil, J., & D’Urso, P. (2024, February). Prescriptive Analytics-based Robust Decision-Making Model for Cyber Disaster Risk Reduction. In 2024 IEEE 3rd International Conference on AI in Cybersecurity (ICAIC) (pp. 1-5). IEEE. https://www.researchgate.net/publication/378271477_Prescriptive_Analytics-based_Robust_Decision-Making_Model_for_Cyber_Disaster_Risk_Reduction Decision-making in cyber security attack scenarios involves deep uncertainty and adversarial decision-making. Robust Decision Making (RDM) uses a…

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Exploratory modelling and analysis to support decision-making under deep uncertainty: A case study from defence resource planning and asset management (2024)

Cite: Kahagalage, S. D., Turan, H. H., Elsawah, S., & Gary, M. S. (2024). Exploratory modelling and analysis to support decision-making under deep uncertainty: A case study from defence resource planning and asset management. Technological Forecasting and Social Change, 200, 123150. url: https://www.sciencedirect.com/science/article/pii/S0040162523008351?via%3Dihub Abstract Emerging approaches and tools in the literature for…

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Self-Adaptive Multi-Objective Climate Policies Align Mitigation and Adaptation Strategies (2022)

Carlino, A., Tavoni, M., & Castelletti, A. (2022). Self-adaptive multi-objective climate policies align mitigation and adaptation strategies. Earth’s Future, 10, e2022EF002767. https://doi.org/10.1029/2022EF002767 Intensifying climate change impacts can divert the economic resources away from emission reduction toward adaptation to reduce rising damages, jeopardizing temperature stabilization within safe levels. Indeed, the traditional…

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Simulation-Based Optimization: Implications of Complex Adaptive Systems and Deep Uncertainty (2022)

Tolk, Andreas. 2022. “Simulation-Based Optimization: Implications of Complex Adaptive Systems and Deep Uncertainty” Information 13, no. 10: 469. https://doi.org/10.3390/info13100469   Within the modeling and simulation community, simulation-based optimization has often been successfully used to improve productivity and business processes. However, the increased importance of using simulation to better understand complex adaptive systems…

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Climate-aware decision-making: lessons for electric grid infrastructure planning and operations

Brockway, Anna M, Liyang Wang, Laurel N Dunn, Duncan Callaway, and Andrew Jones. “Climate-Aware Decision-Making: Lessons for Electric Grid Infrastructure Planning and Operations.” Environmental Research Letters 17, no. 7 (June 28, 2022): 073002. https://doi.org/10.1088/1748-9326/ac7815. Climate change poses significant risks to large-scale infrastructure systems and brings considerable uncertainties that challenge historical…

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post-MORDM: Mapping policies to synthesize optimization and robustness results for decision-maker compromise (2022)

Bonham, N., Kasprzyk, J., Zagona, E., 2022. post-MORDM: Mapping policies to synthesize optimization and robustness results for decision-maker compromise. Environ. Model. Softw. 157, 105491. https://doi.org/10.1016/j.envsoft.2022.105491 This paper introduces post-MORDM, a decision-support framework that augments Many Objective Robust Decision Making (MORDM). MORDM often creates an intractable number of environmental management policies,…

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From optimal to robust climate strategies: expanding integrated assessment model ensembles to manage economic, social, and environmental objectives (2022)

Ferrari Luca, Angelo Carlino, Paolo Gazzotti, Massimo Tavoni, and Andrea Castelletti. 2022. “From Optimal to Robust Climate Strategies: Expanding Integrated Assessment Model Ensembles to Manage Economic, Social, and Environmental Objectives.” Environmental Research Letters. doi: https://doi.org/10.1088/1748-9326/ac843b   Cost-benefit integrated assessment models generate welfare-maximizing mitigation pathways under a set of assumptions to…

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Decision Science Can Help Address the Challenges of Long-Term Planning in the Colorado River Basin (2022)

Rebecca Smith, Edith Zagona, Joseph Kasprzyk, Nathan Bonham, Elliot Alexander, Alan Butler, James Prairie, Carly Jerla http://doi.org/10.1111/1752-1688.12985 “Deep uncertainty” is a term that describes planning contexts in which it is impossible to determine the likelihood of any given set of future conditions, there are conflicting performance objectives and priorities, and…

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Visualizations for decision support in scenario-based multiobjective optimization

Shavazipour, Babooshka, Manuel López-Ibáñez, and Kaisa Miettinen. “Visualizations for decision support in scenario-based multiobjective optimization.” Information Sciences 578 (2021): 1-21.  https://doi.org/10.1016/j.ins.2021.07.025 Abstract We address challenges of decision problems when managers need to optimize several conflicting objectives simultaneously under uncertainty. We propose visualization tools to support the solution of such scenario-based multiobjective optimization…

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New Article: Robust climate change adaptation for environmental flows in the Goulburn River, Australia

https://www.frontiersin.org/articles/10.3389/fenvs.2021.789206/abstract Climate change presents severe risks for the implementation and success of environmental flows worldwide. Current environmental flow assessments tend to assume climate stationarity, so there is an urgent need for robust environmental flow programs that allow adaptation to changing flow regimes due to climate change. Designing and implementing robust…

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