Relevant bibliographies by topics / Scenario uncertainty

Academic literature on the topic 'Scenario uncertainty'

Author: Grafiati
Published: 1 June 2024

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Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Journal articles on the topic "Scenario uncertainty":

1

Pollack-Johnson, Bruce, and Matthew J. Liberatore. "Project Planning under Uncertainty Using Scenario Analysis." Project Management Journal 36, no. 1 (March 2005): 15–26. http://dx.doi.org/10.1177/875697280503600103.

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An important component of risk management relates to project schedule uncertainty. To address this issue, a scenario (i.e., macro-level approach) for modeling and analyzing projects with significant uncertainty in their network structure and/or durations of some activities is presented. This approach requires that a set of project network scenarios is able to be identified, each with an assessed probability of occurrence. These scenarios might differ according to the results of uncertain events that could occur during the course of the project, uncertain activity durations (whether independent or dependent), finite loops where repeated activities can have different durations, or a combination of these. Advantages of our approach include the use of standard methods and software, as well as greater accessibility to, and likelihood of, the use of uncertainty analysis in project planning. Several examples are used to illustrate the suggested approach.
2

Jansen van Vuuren, David. "Valuing specialised property: cost vs profits method uncertainty." Journal of Property Investment & Finance 34, no. 6 (September 5, 2016): 655–63. http://dx.doi.org/10.1108/jpif-06-2016-0048.

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Purpose The purpose of this paper is to compare the value outcomes of the cost approach to the DCF profits method when valuing specialised property under different scenarios as a test for choice of method or model uncertainty; and to quantify valuation uncertainty under each scenario and to argue for an increasing adoption of the profits method of valuation. Design/methodology/approach A qualitative case study approach was used to analyse four physical valuations performed in practice under four specific scenarios, namely, a business-as-usual scenario, an underperforming business scenario, an expanding capacity scenario and a combined business-as-usual funding a start-up joint venture scenario. Findings The cost approach relative to the DCF profits approach consistently under-values specialised property under business-as-usual and business expanding scenarios while it over-values in instances of underperforming business scenario. Practical implications Financial institutions that predominantly uses or accepts the cost approach for valuing specialised property should consider adopting the DCF profits approach as the default approach when valuing for mortgage lending purposes. Business owners of specialised properties should contract practitioners knowledgeable and skilled in the application of the DCF profits method. Originality/value This paper quantifies choice of method or model uncertainty of four different scenarios of specialised properties where both the cost approach and DCF profits methods of valuation were employed. It suggests the adoption of the DCF profits method as the default method of valuation for specialised property.
3

Cambou, Mathieu, and Damir Filipović. "MODEL UNCERTAINTY AND SCENARIO AGGREGATION." Mathematical Finance 27, no. 2 (June 19, 2015): 534–67. http://dx.doi.org/10.1111/mafi.12097.

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Yip, Stan, Christopher A. T. Ferro, David B. Stephenson, and Ed Hawkins. "A Simple, Coherent Framework for Partitioning Uncertainty in Climate Predictions." Journal of Climate 24, no. 17 (September 2011): 4634–43. http://dx.doi.org/10.1175/2011jcli4085.1.

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A simple and coherent framework for partitioning uncertainty in multimodel climate ensembles is presented. The analysis of variance (ANOVA) is used to decompose a measure of total variation additively into scenario uncertainty, model uncertainty, and internal variability. This approach requires fewer assumptions than existing methods and can be easily used to quantify uncertainty related to model–scenario interaction—the contribution to model uncertainty arising from the variation across scenarios of model deviations from the ensemble mean. Uncertainty in global mean surface air temperature is quantified as a function of lead time for a subset of the Coupled Model Intercomparison Project phase 3 ensemble and results largely agree with those published by other authors: scenario uncertainty dominates beyond 2050 and internal variability remains approximately constant over the twenty-first century. Both elements of model uncertainty, due to scenario-independent and scenario-dependent deviations from the ensemble mean, are found to increase with time. Estimates of model deviations that arise as by-products of the framework reveal significant differences between models that could lead to a deeper understanding of the sources of uncertainty in multimodel ensembles. For example, three models show a diverging pattern over the twenty-first century, while another model exhibits an unusually large variation among its scenario-dependent deviations.
5

Mo, Mingshan, Xinrui Xiong, Yunlong Wu, and Zuyao Yu. "Deep-Reinforcement-Learning-Based Low-Carbon Economic Dispatch for Community-Integrated Energy System under Multiple Uncertainties." Energies 16, no. 22 (November 20, 2023): 7669. http://dx.doi.org/10.3390/en16227669.

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A community-integrated energy system under a multiple-uncertainty low-carbon economic dispatch model based on the deep reinforcement learning method is developed to promote electricity low carbonization and complementary utilization of community-integrated energy. A demand response model based on users’ willingness is proposed for the uncertainty of users’ demand response behavior; a training scenario set of a reinforcement learning agent is generated with a Latin hypercube sampling method for the uncertainties of power, load, temperature, and electric vehicle trips. Based on the proposed demand response model, low-carbon economic dispatch of the community-integrated energy system under multiple uncertainties is achieved by training the agent to interact with the environment in the training scenario set and reach convergence after 250 training rounds. The simulation results show that the reinforcement learning agent achieves low-carbon economic dispatch under 5%, 10%, and 15% renewable energy/load fluctuation scenarios, temperature fluctuation scenarios, and uncertain scenarios of the number of trips, time periods, and mileage of electric vehicles, with good generalization performance under uncertain scenarios.
6

Engelberg, Daniel. "The value of scenario discovery in land-use modeling: An automated vehicle test case." Journal of Transport and Land Use 17, no. 1 (May 9, 2024): 321–49. http://dx.doi.org/10.5198/jtlu.2024.2401.

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Long-range planning is an uncertain endeavor. This is especially true for urban regions, small ships in a global urban storm that are too small to influence macro policies and without the land-use powers of local governments. Exploratory scenarios, the established practice for planning under deep uncertainty, have inspired stakeholders to consider multiple futures but have fallen short of identifying robust and contingent policies. We need new tools to plan under conditions of deep uncertainty. Scenario discovery is a technique for using simulation models to explore the performance of policy options across uncertain scenarios. This paper presents an application of scenario discovery in land-use modeling and asks what this computationally intensive approach offers relative to a more circumscribed exploration of uncertainty space. The introduction of autonomous vehicles (AVs) and their associated impacts on land use provide a test case demonstrating this method, as well as a topic of substantive concern. This research concludes that scenario discovery is particularly valuable for identifying the conditions under which contingent policies are likely to succeed. In terms of AV policy, this research establishes that forward-thinking, transit-oriented-development strategies can mitigate spatial dispersion while also reducing overall housing costs. In addition, I find that AVs may blunt the impacts of some current policy tools if they extend the distance individuals are willing to travel to work.
7

Choi, Byung-Cheon, and Myoung-Ju Park. "Min-Max Regret Version of the Linear Time–Cost Tradeoff Problem with Multiple Milestones and Completely Ordered Jobs." Asia-Pacific Journal of Operational Research 32, no. 05 (October 2015): 1550039. http://dx.doi.org/10.1142/s0217595915500396.

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We consider a linear time–cost tradeoff problem with multiple milestones and uncertain processing times such that all jobs are completely ordered. The performance measure is expressed as the sum of total weighted number of tardy jobs and total crashing cost. The processing times uncertainty is described through two types of scenarios: discrete and interval scenarios. The objective is to minimize maximum deviation from optimality over all scenarios. For the discrete scenario case, we prove its NP-hardness, develop a pseudo-polynomial time approach, and present a polynomially solvable case. Finally, we show that the interval scenario case is also NP-hard.
8

Carneiro, Joana, Dália Loureiro, Marta Cabral, and Dídia Covas. "Integrating Uncertainty in Performance Assessment of Water Distribution Networks by Scenario Building." Water 16, no. 7 (March 28, 2024): 977. http://dx.doi.org/10.3390/w16070977.

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This paper presents and demonstrates a novel scenario-building methodology that integrates contextual and future time uncertainty into the performance assessment of water distribution networks (WDNs). A three-step approach is proposed: (i) System context analysis, identifying the main key factors that impact the WDN performance; (ii) Scenario definition, identifying the implicated WDN variables, describing its possible evolution, and conjugating them to further establish the reference scenario and the two most relevant and opposite ones; and (iii) Scenario modelling, simulating the WDN behaviour for those scenarios. The obtained spatial and temporal hydraulic results are further used to calculate performance metrics. The methodology is applied to a real WDN to assess resilience performance considering infrastructure asset robustness (real water loss performance indicator), service reliability (minimum pressure index), and service flexibility (network resilience index). A new formulation to assess the metric evolution over time is proposed, deducting the further-away performance results by using an uncertainty weight. The results demonstrate that the increase in metric amplitude for the opposite scenarios over time highlights future uncertainty, reflecting context uncertainty, and the comparison of metric spatial distribution (i.e., at the pipe/node levels) highlights critical areas with higher associated uncertainty.
9

Smorkalova, Tatyana L., Lyudmila V. Tarasova, and Olga S. Solodukhina. "GENDER-SPECIFIC LIFE SCENARIOS IN INDIVIDUALS WITH DIFFERENT LEVELS OF TOLERANCE TO UNCERTAINTY." Russian Journal of Education and Psychology 14, no. 5 (October 31, 2023): 109–25. http://dx.doi.org/10.12731/2658-4034-2023-14-5-109-125.

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Purpose. Currently, the scenario line of research in personality psychology seems to be particularly promising, since this line of research allows us to identify the specific features of the transformation of the conscious construction of human life paths under changing conditions of uncertainty. The aim of the study is to determine the gender specificity of life scenarios in individuals with different levels of tolerance to uncertainty. Materials and Methods. The sampling consisted of 200 people with different levels of tolerance towards uncertainty. The methods of the study included the semantic differential Lifestyle by V.P. Serkin and the New Questionnaire of Tolerance Towards Uncertainty by T.V. Kornilova. The data obtained were processed by means of factor analysis with the help of the program IBM SPSS Statistics 23. Results. The results showed that the life scenarios of people with different levels of tolerance to uncertainty are gender-specific: men with a high tolerance to uncertainty show predominant characteristics of the scenario associated with an active life position and the search for novelty, whereas women show a scenario aimed at activity in the social sphere (the desire to actively participate in the fate of others, to help and support). Men with a low tolerance towards uncertainty show such scenario patterns as striving for security, stability and predictability of events, while women – in addition to striving for a convenient, comfortable life – show tactical patterns: emotional restraint and calculation. Field of results application. The results of the study can be used in socio-psychological training and counselling to identify and correct an individual’s life scenario.
10

Marzeion, B., A. H. Jarosch, and M. Hofer. "Past and future sea-level change from the surface mass balance of glaciers." Cryosphere Discussions 6, no. 4 (August 6, 2012): 3177–241. http://dx.doi.org/10.5194/tcd-6-3177-2012.

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Abstract. We present a model of the global surface mass balance of glaciers, based on the reconstruction and projection of the surface mass balance of all the world's individual glaciers. The model is validated using a leave-one-glacier-out cross validation scheme using 3997 observed surface mass balances of 255 glaciers, and against 756 geodetically observed, temporally integrated volume and surface area changes of 341 glaciers. Between 1902 and 2009, the world's glaciers are reconstructed to have lost mass corresponding to 114 ± 5 mm sea level equivalent (SLE). During the 21st century, they are projected to loose additionally between 148 ± 35 mm SLE (scenario RCP26), 166 ± 42 mm SLE (scenario RCP45), 175 ± 40 mm SLE (scenario RCP60), to 217 ± 47 mm SLE (scenario RCP85). Based on the extended RCP scenarios, glaciers are projected to approach a new equilibrium towards the end of the 23rd century, after having lost between 248 ± 66 mm SLE (scenario RCP26), 313 ± 50 mm SLE (scenario RCP45), to 424 ± 46 mm SLE (scenario RCP85). Up until approximately 2100, ensemble uncertainty within each scenario is the biggest source of uncertainty for the future glacier mass loss; after that, the difference between the scenarios takes over as the biggest source of uncertainty. Rates of mass loss are projected to peak between 2050 and 2100, depending on the scenario.
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Journal articles Dissertations / Theses Books

Dissertations / Theses on the topic "Scenario uncertainty":

1

Mott, Lacroix Kelly, Ashley Hullinger, Mark Apel, William Brandau, and Sharon B. Megdal. "Using Scenario Planning to Prepare for Uncertainty in Rural Watersheds." College of Agriculture, University of Arizona (Tucson, AZ), 2015. http://hdl.handle.net/10150/593579.

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10 pp.
Planning for an uncertain future presents many challenges. Thinking systematically and creatively about what is in store through a process called scenario planning can help illuminate options for action and improve decision-making. This guide focuses on a process for developing scenarios to help communities and watershed groups explore what might happen in the years to come, make more informed decisions today, and build a watershed management process. The systematic approach to scenario planning described here is based on the lessons learned through a yearlong scenario planning process in the Upper Gila Watershed in southeastern Arizona and Water Resource Research Center’s (WRRC) research on scenario planning.
2

Cooksey, Kenneth Daniel. "A portfolio approach to design in the presence of scenario-based uncertainty." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/49036.

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Current aircraft conceptual design practices result in the selection of a single (hopefully) Pareto optimal design to be carried forward into preliminary design. This paradigm is based on the assumption that carrying a significant number of concepts forward is too costly and thus early down-selection between competing concepts is necessary. However, this approach requires that key architectural design decisions which drive performance and market success are fixed very early in the design process, sometimes years before the aircraft actually goes to market. In the presence of uncertainty, if the design performance is examined for individual scenarios as opposed to measuring performance of the design with aggregate statistics, the author finds that the single concept approach can lead to less than desirable design outcomes. This thesis proposes an alternate conceptual design paradigm which leverages principles from economics (specifically the Nobel prize-winning modern portfolio theory) to improve design outcomes by intelligently selecting a small well diversified portfolio of concepts to carry forward through preliminary design, thus reducing the risk from external events that are outside of the engineer’s control. This alternate paradigm is expected to result in an increase in the overall profit by increasing the probability that the final design matches market needs at the time it goes to market. This thesis presents a portfolio based design approach, which leverages dynamic programming to enable a stochastic optimization of alternative portfolios of concepts. This optimization returns an optimized portfolio of concepts which are iteratively pruned to improve design outcomes in the presence of scenario-driven uncertainties. While dynamic programming is identified as a means for doing a stochastic portfolio optimization, dynamic programming is an analytical optimization process which suffers heavily from the curse of dimensionality. As a result, a new hybrid stochastic optimization process called the Evolutionary Cooperative Optimization with Simultaneous Independent Sub-optimization (ECOSIS) has been introduced. The ECOSIS algorithm leverages a co-evolutionary algorithm to optimize a multifaceted problem under uncertainty. ECOSIS allows for a stochastic portfolio optimization including the desired benefit-to-cost tradeoff for a well-diversified portfolio at the size and scope required for use in design problems. To demonstrate the applicability and value of a portfolio based design approach, an example application of the approach to the selection of a new 300 passenger aircraft is presented.
3

Tshimanga, Raphael Muamba. "Hydrological uncertainty analysis and scenario-based streamflow modelling for the Congo River Basin." Thesis, Rhodes University, 2012. http://hdl.handle.net/10962/d1006158.

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The effects of climate and environmental change are likely to exacerbate water stress in Africa over the next five decades. It appears obvious, therefore, that large river basins with considerable total renewable water resources will play a prominent role in regional cooperation to alleviate the pressure of water scarcity within Africa. However, managing water resources in the large river basins of Africa involves problems of data paucity, lack of technical resources and the sheer scale of the problem. These river basins are located in regions that are characterized by poverty, low levels of economic development and little food security. The rivers provide multiple goods and services that include hydro-power, water supply, fisheries, agriculture, transportation, and maintenance of aquatic ecosystems. Sustainable water resources management is a critical issue, but there is almost always insufficient data available to formulate adequate management strategies. These basins therefore represent some of the best test cases for the practical application of the science associated with the Predictions in Ungauged Basins (PUB). The thesis presents the results of a process-based hydrological modelling study in the Congo Basin. One of the primary objectives of this study was to establish a hydrological model for the whole Congo Basin, using available historical data. The secondary objective of the study was to use the model and assess the impacts of future environmental change on water resources of the Congo Basin. Given the lack of adequate data on the basin physical characteristics, the preliminary work consisted of assessing available global datasets and building a database of the basin physical characteristics. The database was used for both assessing relationships of similarities between features of physiographic settings in the basin (Chapters 3 and 4), and establishing models that adequately represent the basin hydrology (Chapters 5, 6, and 7). The representative model of the Congo Basin hydrology was then used to assess the impacts of future environmental changes on water resources availability of the Congo Basin (Chapter 8). Through assessment of the physical characteristics of the basin, relationships of similarities were used to determine homogenous regions with regard to rainfall variability, physiographic settings, and hydrological responses. The first observation that comes from this study is that these three categories of regional groups of homogenous characteristics are sensible with regards to their geographical settings, but the overlap and apparent relationships between them are weak. An explanation of this observation is that there are insufficient data, particularly associated with defining sub-surface processes, and it is possible that additional data would have assisted in the discrimination of more homogenous groups and better links between the different datasets. The model application in this study consisted of two phases: model calibration, using a manual approach, and the application of a physically-based a priori parameter estimation approach. While the first approach was designed to assess the general applicability of the model and identify major errors with regard to input data and model structure, the second approach aimed to establish an understanding of the processes and identify useful relationships between the model parameters and the variations in real hydrological processes. The second approach was also designed to quantify the sensitivity of the model outputs to the parameters of the model and to encompass information sharing between the basin physical characteristics and quantifying the parameters of the model. Collectively, the study’s findings show that these two approaches work well and are appropriate to represent the real hydrological processes of Congo Basin. The secondary objective of this study was achieved by forcing the hydrological model developed for the Congo Basin with downscaled Global Climate Model (GCMs) data in order to assess scenarios of change and future possible impacts on water resources availability within the basin. The results provide useful lessons in terms of basin-wide adaptation measures to future climates. The lessons suggest that there is a risk of developing inappropriate adaptation measures to future climate change based on large scale hydrological response, as the response at small scales shows a completely different picture from that which is based on large scale predictions. While the study has concluded that the application of the hydrological model has been successful and can be used with some degree of confidence for enhanced decision making, there remain a number of uncertainties and opportunities to improve the methods used for water resources assessment within the basin. The focus of future activities from the perspective of practical application should be on improved access to data collection to increase confidence in model predictions, on dissemination of the knowledge generated by this study, and on training in the use of the developed water resources assessment techniques.
4

Robinson, Amanda Jane. "Uncertainty in hydrological scenario modelling : an investigation using the Mekong River Basin, SE Asia." Thesis, University College London (University of London), 2018. http://discovery.ucl.ac.uk/10046108/.

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This thesis investigates sources of uncertainty in hydrological scenario modelling. It quantifies the extent to which decisions made during the modelling process affect river flow projections under climate change. Sources of uncertainty explored include choice of: General Circulation Model (GCM) for generation of climate projections; hydrological model code; potential evapotranspiration (PET) method; spatial distribution of meteorological inputs within the hydrological model; and baseline precipitation dataset. The Mekong River Basin is employed as a case study site. Initially a MIKE SHE model is developed for the Mekong using, where possible, the same data as an earlier model (SLURP). Climate scenarios investigated include a set based on a 2 °C increase in global mean temperature simulated by seven GCMs. There are considerable differences in scenario discharges between GCMs, ranging from catchment-wide increases or decreases in mean discharge, to spatially varying responses. Inter-GCM differences are largely driven by differences in precipitation, rather than PET or temperature. Results from MIKE SHE, SLURP and Mac-PDM.09 (a global hydrological model) are compared. Although inter-hydrological model uncertainty is evident and sometimes considerable, its magnitude is generally smaller than GCM uncertainty. The MIKE SHE model is then recalibrated to provide five further models, each employing alternative PET methods. PET method impacts scenario changes in PET and hence scenario discharges. However, GCM-related uncertainty for change in mean discharge is on average ~3.5 times greater than PET method-related uncertainty. Additional MIKE SHE models are developed using alternative meteorological input spatial distributions and an alternative baseline precipitation dataset. These sources of uncertainty are comparable in magnitude; both are much smaller than PET- and GCM-related uncertainty. Climate impact assessment using one MIKE SHE model and an ensemble of 41 CMIP5 GCMs for the RCP4.5 scenario provides further confirmation that GCMrelated uncertainty is the dominant source of uncertainty for Mekong river flow projections.
5

Mahadevan, Srisudha. "Network Selection Algorithm for Satisfying Multiple User Constraints Under Uncertainty in a Heterogeneous Wireless Scenario." University of Cincinnati / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1302550606.

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6

Calfa, Bruno Abreu. "Data Analytics Methods for Enterprise-wide Optimization Under Uncertainty." Research Showcase @ CMU, 2015. http://repository.cmu.edu/dissertations/575.

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This dissertation primarily proposes data-driven methods to handle uncertainty in problems related to Enterprise-wide Optimization (EWO). Datadriven methods are characterized by the direct use of data (historical and/or forecast) in the construction of models for the uncertain parameters that naturally arise from real-world applications. Such uncertainty models are then incorporated into the optimization model describing the operations of an enterprise. Before addressing uncertainty in EWO problems, Chapter 2 deals with the integration of deterministic planning and scheduling operations of a network of batch plants. The main contributions of this chapter include the modeling of sequence-dependent changeovers across time periods for a unitspecific general precedence scheduling formulation, the hybrid decomposition scheme using Bilevel and Temporal Lagrangean Decomposition approaches, and the solution of subproblems in parallel. Chapters 3 to 6 propose different data analytics techniques to account for stochasticity in EWO problems. Chapter 3 deals with scenario generation via statistical property matching in the context of stochastic programming. A distribution matching problem is proposed that addresses the under-specification shortcoming of the originally proposed moment matching method. Chapter 4 deals with data-driven individual and joint chance constraints with right-hand side uncertainty. The distributions are estimated with kernel smoothing and are considered to be in a confidence set, which is also considered to contain the true, unknown distributions. The chapter proposes the calculation of the size of the confidence set based on the standard errors estimated from the smoothing process. Chapter 5 proposes the use of quantile regression to model production variability in the context of Sales & Operations Planning. The approach relies on available historical data of actual vs. planned production rates from which the deviation from plan is defined and considered a random variable. Chapter 6 addresses the combined optimal procurement contract selection and pricing problems. Different price-response models, linear and nonlinear, are considered in the latter problem. Results show that setting selling prices in the presence of uncertainty leads to the use of different purchasing contracts.
7

Hollmann, Dominik. "Supply chain network design under uncertainty and risk." Thesis, Brunel University, 2011. http://bura.brunel.ac.uk/handle/2438/6407.

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We consider the research problem of quantitative support for decision making in supply chain network design (SCND). We first identify the requirements for a comprehensive SCND as (i) a methodology to select uncertainties, (ii) a stochastic optimisation model, and (iii) an appropriate solution algorithm. We propose a process to select a manageable number of uncertainties to be included in a stochastic program for SCND. We develop a comprehensive two-stage stochastic program for SCND that includes uncertainty in demand, currency exchange rates, labour costs, productivity, supplier costs, and transport costs. Also, we consider conditional value at risk (CV@R) to explore the trade-off between risk and return. We use a scenario generator based on moment matching to represent the multivariate uncertainty. The resulting stochastic integer program is computationally challenging and we propose a novel iterative solution algorithm called adaptive scenario refinement (ASR) to process the problem. We describe the rationale underlying ASR, validate it for a set of benchmark problems, and discuss the benefits of the algorithm applied to our SCND problem. Finally, we demonstrate the benefits of the proposed model in a case study and show that multiple sources of uncertainty and risk are important to consider in the SCND. Whereas in the literature most research is on demand uncertainty, our study suggests that exchange rate uncertainty is more important for the choice of optimal supply chain strategies in international production networks. The SCND model and the use of the coherent downside risk measure in the stochastic program are innovative and novel; these and the ASR solution algorithm taken together make contributions to knowledge.
8

Persson, Klas. "Quantifying pollutant spreading and the risk of water pollution in hydrological catchments : A solute travel time-based scenario approach." Doctoral thesis, Stockholms universitet, Institutionen för naturgeografi och kvartärgeologi (INK), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-63465.

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The research presented in the thesis develops an approach for the estimation and mapping of pollutant spreading in catchments and the associated uncertainty and risk of pollution. The first step in the approach is the quantification and mapping of statistical and geographical distributions of advective solute travel times from pollutant input locations to downstream recipients. In the second step the travel time distributions are used to quantify and map the spreading of specific pollutants and the related risk of water pollution. In both steps, random variability of transport properties and processes is accounted for within a probabilistic framework, while different scenarios are used to account for statistically unquantifiable uncertainty about system characteristics, processes and future developments. This scenario approach enables a transparent analysis of uncertainty effects that is relatively easy to interpret. It also helps identify conservative assumptions and pollutant situations for which further investigations are most needed in order to reduce the uncertainty. The results for different investigated scenarios can further be used to assess the total risk to exceed given water quality standards downstream of pollutant sources. Specific thesis results show that underestimation of pollutant transport variability, and in particular of those transport pathways with much shorter than average travel times, may lead to substantial underestimation of pollutant spreading in catchment areas. By contrast, variations in pollutant attenuation rate generally lead to lower estimated spreading than do constant attenuation conditions. A scenario of constant attenuation rate and high travel time variability, with a large fraction of relatively short travel times, therefore appears to be a reasonable conservative scenario to use when information is lacking for more precise determination of actual transport and attenuation conditions.
9

Valente, Christian. "Design and architecture of a stochastic programming modelling system." Thesis, Brunel University, 2011. http://bura.brunel.ac.uk/handle/2438/6249.

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Decision making under uncertainty is an important yet challenging task; a number of alternative paradigms which address this problem have been proposed. Stochastic Programming (SP) and Robust Optimization (RO) are two such modelling ap-proaches, which we consider; these are natural extensions of Mathematical Pro-gramming modelling. The process that goes from the conceptualization of an SP model to its solution and the use of the optimization results is complex in respect to its deterministic counterpart. Many factors contribute to this complexity: (i) the representation of the random behaviour of the model parameters, (ii) the interfac-ing of the decision model with the model of randomness, (iii) the difficulty in solving (very) large model instances, (iv) the requirements for result analysis and perfor-mance evaluation through simulation techniques. An overview of the software tools which support stochastic programming modelling is given, and a conceptual struc-ture and the architecture of such tools are presented. This conceptualization is pre-sented as various interacting modules, namely (i) scenario generators, (ii) model generators, (iii) solvers and (iv) performance evaluation. Reflecting this research, we have redesigned and extended an established modelling system to support modelling under uncertainty. The collective system which integrates these other-wise disparate set of model formulations within a common framework is innovative and makes the resulting system a powerful modelling tool. The introduction of sce-nario generation in the ex-ante decision model and the integration with simulation and evaluation for the purpose of ex-post analysis by the use of workflows is novel and makes a contribution to knowledge.
10

Minton, Mark A. "Uncertainty and sensitivity analysis of a fire-induced accident scenario involving binary variables and mechanistic codes." Thesis, Cambridge Massachusetts Institute of Technology, 2010. http://hdl.handle.net/10945/4939.

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CIVINS
Approved for public release; distribution is unlimited
In response to the transition by the United States Nuclear Regulatory Commission (NRC) to a risk-informed, performance-based fire protection rulemaking standard, Fire Probabilistic Risk Assessment (PRA) methods have been improved, particularly in the areas of advanced fire modeling and computational methods. In order to gain a more meaningful insight into the methods currently in practice, it was decided that a scenario incorporating the various elements of uncertainty specific to a fire PRA would be analyzed. Fire induced Main Control Room (MCR) abandonment scenarios are a significant contributor to the total Core Damage Frequency (CDF) estimate of many operating nuclear power plants. This report details the simultaneous application of state-of-the-art model and parameter uncertainty techniques to develop a defensible distribution of the probability of a forced MCR abandonment caused by a fire within a MCR benchboard. This report details the simultaneous application of state-of-the-art model and parameter uncertainty techniques to develop a defensible distribution of the probability of a forced MCR abandonment caused by a fire within a MCR.
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Books on the topic "Scenario uncertainty":

1

Georgantzas, Nicholas C. Scenario-driven planning: Learning to manage strategic uncertainty. Westport, Conn: Quorum Books, 1995.

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2

Hlaváček, Ivan. Uncertain input data problems and the worst scenario method. Amsterdam: Elsevier, 2004.

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3

Lantermann, Ernst-Dieter. Ravenhorst: Gefühle, Werte und Unbestimmtheit im Umgang mit einem ökologischen Scenario. München: Quintessenz, 1992.

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Hammitt, James K. Subjective-probability-based scenarios for uncertain input parameters: Stratospheric ozone depletion. Santa Monica, CA: Rand, 1990.

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Hammitt, James K. Subjective probability based scenarios for uncertain input parameters: Stratospheric ozone depletion. Santa Monica, CA: Rand, 1990.

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Schwartz, Peter. The art of the long view: Scenario planning - protecting your company against an uncertain future. London: Century Business, 1992.

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Schwartz, Peter, and Peter Schwartz. The art of the long view: Planning for the future in an uncertain world. New York: Currency Doubleday, 1995.

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Schwartz, Peter. The art of the long view: Planning for the future in an uncertain world. New York: Currency Doubleday, 1995.

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Schwartz, Peter. The art of the long view: Planning for the future in an uncertain world. Chichester: Wiley, 1998.

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Campi, Marco C., and Simone Garatti. Introduction to the Scenario Approach. Society for Industrial and Applied Mathematics, 2019.

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Book chapters on the topic "Scenario uncertainty":

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Cuypers, Paul W. M. "Scenario uncertainty." In Mastering Project Uncertainty, 117–35. New York: Routledge, 2023. http://dx.doi.org/10.4324/9781003431961-10.

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Garvey, Bruce. "Scenario Derivatives First, Second, and Third Order Scenarios: Generic (Landscape) Variables." In Uncertainty Deconstructed, 151–72. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08007-4_8.

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Petrakis, Panagiotis E., and Dimitra P. Konstantakopoulou. "Strategic Scenario Thinking." In Uncertainty in Entrepreneurial Decision Making, 141–53. New York: Palgrave Macmillan US, 2015. http://dx.doi.org/10.1057/9781137460790_10.

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Humzah, Dowshan. "An Exploratory Scenario Case Study: Social Mobility and Inequality." In Uncertainty Deconstructed, 217–32. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08007-4_12.

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Buff, Robert. "Scenario-Based Evaluation and Uncertainty." In Springer Finance, 33–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-56323-2_4.

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Wulf, Torsten, Philip Meissner, Christian Brands, and Stephan Stubner. "Scenario-based strategic planning: A new approach to coping with uncertainty." In Scenario-based Strategic Planning, 43–66. Wiesbaden: Springer Fachmedien Wiesbaden, 2013. http://dx.doi.org/10.1007/978-3-658-02875-6_3.

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Calafiore, Giuseppe Carlo. "Scenario Optimization Methods in Portfolio Analysis and Design." In Optimal Financial Decision Making under Uncertainty, 55–87. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41613-7_3.

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Petrakis, Panagiotis E., and Dimitra P. Konstantakopoulou. "Creative Strategic Scenario Thinking under High Uncertainty and Low Nominal Returns." In Uncertainty in Entrepreneurial Decision Making, 167–84. New York: Palgrave Macmillan US, 2015. http://dx.doi.org/10.1057/9781137460790_12.

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Molina, Carlos, Belen Prados-Suárez, and Daniel Sanchez. "Scenario Query Based on Association Rules (SQAR)." In Information Processing and Management of Uncertainty in Knowledge-Based Systems, 537–48. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40596-4_45.

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Guillaume, Romain, and Paweł Zieliński. "Decision Making under Scenario Uncertainty in a Requirement Planning." In Communications in Computer and Information Science, 104–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31724-8_12.

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Conference papers on the topic "Scenario uncertainty":

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Dani, K. C., V. K. Baskaran, D. K. Gupta, and A. M. Urkude. "Hydrocarbon Risk and Uncertainty: Indian Scenario." In International Petroleum Technology Conference. International Petroleum Technology Conference, 2013. http://dx.doi.org/10.2523/16759-ms.

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Dani, K. C., V. K. Baskaran, D. K. Gupta, and A. M. Urkude. "Hydrocarbon Risk and Uncertainty: Indian Scenario." In International Petroleum Technology Conference. International Petroleum Technology Conference, 2013. http://dx.doi.org/10.2523/iptc-16759-ms.

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Caers, Jef. "Data inversion under geological scenario uncertainty." In SEG Technical Program Expanded Abstracts 2012. Society of Exploration Geophysicists, 2012. http://dx.doi.org/10.1190/segam2012-0055.1.

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Mair Sdn Bhd, Dylan, and Lee Hong Shien. "Scenario-based Velocity Modeling forDepth Conversion Uncertainty." In PGCE 2005. European Association of Geoscientists & Engineers, 2005. http://dx.doi.org/10.3997/2214-4609-pdb.257.11.

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Bentley, M. R., and T. J. Woodhead. "Uncertainty Handling Through Scenario-Based Reservoir Modelling." In SPE Asia Pacific Conference on Integrated Modelling for Asset Management. Society of Petroleum Engineers, 1998. http://dx.doi.org/10.2118/39717-ms.

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Bukhanov, N. V., I. I. Alekhin, V. V. Demyanov*, and V. E. Baranov. "Development Scenario Optimization under Geological Description Uncertainty." In Petroleum Geostatistics 2015. Netherlands: EAGE Publications BV, 2015. http://dx.doi.org/10.3997/2214-4609.201413656.

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Figueroa, Vicente Sepulveda, and Carlos Benavides Farias. "Carbon Neutrality Scenario Projection Model under Uncertainty." In 2022 IEEE International Conference on Automation/XXV Congress of the Chilean Association of Automatic Control (ICA-ACCA). IEEE, 2022. http://dx.doi.org/10.1109/ica-acca56767.2022.10005931.

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Callens, Robin R. P., David Moens, and Matthias Faes. "CERTIFIED INTERVAL MODEL UPDATING USING SCENARIO OPTIMISATION." In 5th International Conference on Uncertainty Quantification in Computational Sciences and Engineering. Athens: Institute of Structural Analysis and Antiseismic Research National Technical University of Athens, 2023. http://dx.doi.org/10.7712/120223.10346.19855.

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Sharma, Kailash Chand, Rohit Bhakar, H. P. Tiwari, and Sandeep Chawda. "Scenario based uncertainty modeling of electricity market prices." In 2017 6th International Conference on Computer Applications in Electrical Engineering-Recent Advances (CERA). IEEE, 2017. http://dx.doi.org/10.1109/cera.2017.8343320.

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Milton, Julia, and Daniel E. Hastings. "Scenario-based uncertainty quantification for optical link analysis." In ASCEND 2023. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2023. http://dx.doi.org/10.2514/6.2023-4622.

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Reports on the topic "Scenario uncertainty":

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Hernandez-Abrams, Darixa, Carra Carrillo, and Todd Swannack. Scenario analyses in ecological modeling and ecosystem management. Engineer Research and Development Center (U.S.), July 2022. http://dx.doi.org/10.21079/11681/44840.

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Ecosystem management and restoration practitioners are challenged with complex problems, diverse project goals, multiple management alternatives, and potential future scenarios that change the systems of interest. Scenario analysis aids in forecasting, evaluating, and communicating outcomes of potential management actions under different plausible conditions, such as land-use change or sea level rise. However, little guidance exists for practitioners on the utility and execution of scenario analysis. Therefore, this technical note highlights the usefulness of scenario analysis as a tool for addressing uncertainty in potential project outcomes. The mechanics of the scenario-analysis process are explained, and examples of different types of scenario analyses are described for context on the breadth of its use. Lastly, two hypothetical case studies of scenario analysis in ecological modeling are presented showing a semiquantitative approach for assessing anadromous fish and a quantitative approach examining freshwater mussel habitat. Overall, this technical note provides a brief review of the utility and application of scenario analyses in the context of ecological modeling and ecosystem management decision-making.
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Runyon, Amber, Gregor Schuurman, Brecken Robb, Jeremy Littell, Mark Miller, and Joel Reynolds. Climate-resource scenarios to inform climate change adaptation in Wrangell-St. Elias National Park and Preserve: Summary of 2021 climate change scenario planning. National Park Service, 2024. http://dx.doi.org/10.36967/2301920.

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This report illustrates use of scenario planning as a climate change adaptation tool supporting Wrangell-St. Elias National Park and Preserve?s Resource Stewardship Strategy. The primary objective of scenario planning is to help resource managers and scientists make management and planning decisions informed by assessments of critical future uncertainties. This report outlines a process that synthesized future climate projections into three distinct but plausible and relevant climate summaries for the focal area and used them to develop climate-resource scenarios through participatory scenario planning. Initial steps identified the priority resource management topics and the corresponding related climate uncertainties. Next, local climate summaries were used to develop divergent climate futures: those that describe the broadest possible range of plausible conditions while capturing relevant uncertainty. The final phase further developed the climate futures and their resource implications. These participatory scenario planning exercises occurred virtually in fall (August?November) 2021. The climate-resource scenarios informed adaptation strategies in conjunction with the park?s Resource Stewardship Strategy development. The scope and complexity of this effort is unique but elements from the scenarios and resource implications have broad applicability to other large, protected areas in Alaska and Northwest Canada.
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Kucherova, Hanna, Anastasiia Didenko, Olena Kravets, Yuliia Honcharenko, and Aleksandr Uchitel. Scenario forecasting information transparency of subjects' under uncertainty and development of the knowledge economy. [б. в.], October 2020. http://dx.doi.org/10.31812/123456789/4469.

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Topicality of modeling information transparency is determined by the influence it has on the effectiveness of management decisions made by an economic entity in the context of uncertainty and information asymmetry. It has been found that information transparency is a poorly structured category which acts as a qualitative characteristic of information and at certain levels forms an additional spectrum of properties of the information that has been adequately perceived or processed. As a result of structuring knowledge about the factor environment, a fuzzy cognitive model of information transparency was constructed in the form of a weighted digraph. Structural analysis and scenario forecasting of optimal alternatives of the fuzzy cognitive model made it possible to evaluate the classes of factors, identify their limited relations, establish the centrality of the roles of information transparency and information and communication security in the system built and evaluate their importance when modeling the situation self-development. Information visibility, reliability and availability have been found to have the strongest impact on the system. Taking into account different initial weights of the key factors — information transparency and information and communication security — the study substantiates the strategic ways for economic entities to achieve their goals in the context of uncertainty and information asymmetry, which allows us to use this approach as a tool for strategic management in the information environment.
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Meyer, Philip D., Ming Ye, Mark L. Rockhold, Shlomo P. Neuman, and Kirk J. Cantrell. Combined Estimation of Hydrogeologic Conceptual Model, Parameter, and Scenario Uncertainty with Application to Uranium Transport at the Hanford Site 300 Area. Office of Scientific and Technical Information (OSTI), July 2007. http://dx.doi.org/10.2172/921264.

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Rosser, Katy, Iulia Gherman, Erica Kintz, Paul Cook, and Anthony WIlson. Assessment of the risk to consumers as a result of disruption to the cold chain during direct supply of Qurbani meat and offal. Food Standards Agency, June 2022. http://dx.doi.org/10.46756/sci.fsa.nuc910.

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Qurbani is a religious practice that takes place during Eid al-Adha. Consumers practicing Qurbani typically wish to collect meat and red offal within a short time after slaughter, which means these products cannot complete normal chilling processes before leaving the slaughterhouse. This could permit greater growth of pathogens and has the potential to increase the risk of consumer illness. The FSA is working with industry and stakeholder groups to ensure that the risk to consumers under these conditions remains at an acceptable level. To help inform these discussions, the FSA commissioned this assessment to understand the difference in risk from allowing meat and offal to be provided to consumers without the normal chilling process. The microbiological team at the FSA have analysed scientific literature, expert opinion and business and consumer survey data to assess the effect of disrupting the cold chain on pathogens in Qurbani meat. The pathogens that were chosen for inclusion in this assessment are non-typhoidal Salmonella enterica, Shiga toxin-producing Escherichia coli, and Clostridium perfringens. Their growth characteristics and prevalence in beef, lamb and goat meat and offal are discussed. The assessment concluded that given the reported variation in the process, there were two important scenarios with distinct outcomes. In the typical scenario, which is the most likely outcome based on the collected data, there is no significant difference in risk to consumer health compared to normal chilling processes, and the risk level was established as Very Low (“very rare but cannot be excluded”). In a reasonably foreseeable worst-case scenario, Salmonella spp. and STEC levels may increase, presenting an increased risk to the consumer. This risk level was established as Low (“rare but does occur”). We also identified several areas where more evidence would be helpful, and as a result identified a High level of uncertainty in our conclusion.
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Lempert, Robert J., Michelle Miro, and Diogo Prosdocimi. A DMDU Guidebook for Transportation Planning Under a Changing Climate. Edited by Benoit Lefevre and Ernesto Monter Flores. Inter-American Development Bank, February 2021. http://dx.doi.org/10.18235/0003042.

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The effects of climate-related natural hazards pose a significant threat to sustainable development in Latin America and the Caribbean (LAC) region and in particular its transportation sector. Risk Management provides an appropriate framework for assessing and mitigating the impacts of climate change and other climate-related natural hazards on transportation systems and choosing actions to enhance their resilience. However, analysts and policymakers involved in transportation planning, policy, and investment face significant challenges in managing the risks triggered by the effects of climate change. Climate change impacts the lifespan of roads, airports, and railroads as they have time horizons that surpass 40 years, thus making it harder (if not impossible) to forecast with confidence all relevant future events that will affect such infrastructure. In addition, the climate has already changed, so the return frequency of storms, for example, and other extreme events may now be different than suggested by the historical record in ways that are not always currently well understood. Implementing Risk Management under conditions of such uncertainty can prove difficult. Decision Making Under Deep Uncertainty (DMDU) enables Risk Management under conditions of Deep Uncertainty, that is when risks cannot confidently be quantified. This guidebook is aligned with the Disaster and Climate Change Risk Assessment Methodology for IDB projects (IDB 2018) and introduces and provides guidance on applying methods for Decision Making Under Deep Uncertainty (DMDU) to transportation planning. It presents the methodological steps that are necessary for the implementation of DMDU methodologies and reviews several such methods, including scenario planning, Adaptive Pathways, and robust decision making (RDM). This review is geared towards supporting the incorporation of DMDU methods into IDBs transportation sector funding and planning processes.
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Mort Webster. Uncertainty in Integrated Assessment Scenarios. Office of Scientific and Technical Information (OSTI), October 2005. http://dx.doi.org/10.2172/883668.

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Amacher, Gregory S., Olli-Pekka Kuuselaa, and Kwok Ping Tsang. Intensity-Based Permit Quotas and the Business Cycle: Does Flexibility Pay Off? Inter-American Development Bank, December 2013. http://dx.doi.org/10.18235/0011514.

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Tradable permit markets for carbon dioxide (C02) emissions respond to short-run fluctuations in economic activity. To provide stability, both price and quantity interventions have been proposed. This paper focuses on the relative performance of fixed versus intensity allowances in the presence of both productivity and energy price uncertainty. Both instruments achieve the same steady-state emissions reduction target of 20 percent, which is similar to the current policy proposals, and the regulator then chooses the allowance policy that has the lowest expected abatement cost. A standard real business cycle (RBC) model is used to solve for the expected abatement cost under both policies. Expected cost outcomes are compared using data from the U. S. economy as the baseline scenario. Unlike previous studies, this paper's results show that, under a reasonable model calibration, fixed allowances outperform intensity allowances by a cost difference of as much as 30 percent.
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Cavicchia, Rebecca, Jonas Kačkus Tybjerg, Hilma Salonen, Maja Brynteson, Nicola Wendt-Lucas, Sæunn Gísladóttir, and Hjalti Jóhannesson. Ten-year Regional Outlook: Future Perspectives for Electric Aviation in the Nordic Region. Nordregio, March 2024. http://dx.doi.org/10.6027/r2024:81403-2503.

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Electric aviation has gained momentum in the Nordic region in recent years. Given its unique geographical features and strong commitment to climate-neutral transport, the Nordic region represents an ideal testing ground for electric aviation. In five to ten years from now, electric aviation has the potential to become reality, so it is crucial to explore which factors may affect its implementation and how regional development may be impacted. The “Electric Aviation and the Effects on the Nordic Region” project presents a ten-year future scenario for electric aviation in the Nordic region. In this report, we explore future scenarios for five selected Nordic routes and identify the key driving forces behind that transformative shift, as well as the positive and negative impacts of electric aviation. The scenarios were developed through focus group discussions conducted with key stakeholders from each of the five Nordic countries (Denmark, Finland, Iceland, Norway and Sweden). The main findings of the study show that electric aviation is generally perceived positively in the various Nordic countries. However, there are also certain contextual differences relating to whether electric aviation is viewed as a pathway to achieving climate targets and removing emissions, stimulating regional development and accessibility of remote areas, or as a new travel option compared to conventional flights. Even though the general attitude towards electric aviation seems to be positive, scepticism and questions regarding the social acceptance of the new technology emerged, as well as the uncertainty around who will be the investors to kick-off the new technology. Furthermore, the future scenarios suggest that a high level of support from local and national governing bodies is required in order to make electric aviation a viable air transport mode in the Nordic region. The insights of this report are intended both to inform decision-makers and to provide nuanced observations from each Nordic country and explore future pathways towards a sustainable and more integrated Nordic region in line with the 2030 vision of the Nordic Council of Ministers.
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Siddiqui, Afzal S., and Chris Marnay. Addressing an Uncertain Future Using Scenario Analysis. Office of Scientific and Technical Information (OSTI), December 2006. http://dx.doi.org/10.2172/928867.

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