Decision-Based Scenario Clustering - General Bounds for Stochastic Optimization Models
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Explore a novel approach to scenario clustering for stochastic optimization models in this 52-minute DS4DM Coffee Talk. Delve into the challenges of managing uncertainty in decision-making processes and learn how to address the computational complexities arising from large numbers of scenarios. Discover a new clustering method that groups scenarios based on associated decisions, providing an efficient way to derive bounds for stochastic optimization models. Gain insights into how this approach can help decision-makers better understand the relationship between uncertainty and decision-making processes, potentially improving their ability to make informed choices in complex, uncertain environments.
Syllabus
Decision-Based Scenario Clustering - General Bounds for Stochastic Optimization Models, Walter Rei
Taught by
GERAD Research Center