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Center for Nonlinear Studies |
We adapt the Likelihood Robust Optimization method recently proposed by Wang, Glynn, and Ye to examine water allocation under the ambiguous distribution of future rainfall, temperature, and demand. We examine the properties of the model and relate it to coherent risk models and deviations. We also investigate the value of collecting additional data and the cost of finding a solution robust to an ambiguous probability distribution. A decomposition-based solution algorithm to solve the resulting model is given and computational results on a long-term water allocation problem in the southeast area of Tucson are presented.
Host: Feng Pan, D-6, fpan@lanl.gov