Data-Driven Methods for Optimization Under Uncertainty with Application to Water Allocation
Stochastic programming is a mathematical technique for decision making under uncertainty using probabilistic statements in the problem objective and constraints. In practice, the distribution of the unknown quantities are often known only through observed or simulated data. This dissertation discuss...
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| Language: | en_US |
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The University of Arizona.
2013
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| Online Access: | http://hdl.handle.net/10150/311177 |