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Description:: This dissertation investigates a number of models and algorithms in the context of optimization under uncertainty. The focus is on risk-averse optimization, where risk aversion is modeled via stochastic dominance, utility theory, and distributionally robust optimization. We first investigate an investment model with fixed contribution rates, optimize asset-allocation decisions in...
Keyword:: Stochastic Programming, Wasserstein distance, and Distributionally robust optimization
Subject:: Operations research
Creator:: Duque Villarreal, Daniel
Owner:: Scholarly Digital Publishing
Language:: en
Date Uploaded:: 02/01/2021
Date Created:: 2020-01-01
Resource Type:: Dissertation
Alternate Identifier:: etdadmin_upload_763341 and http://dissertations.umi.com/northwestern:15241

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