Many environmental problems are difficult to analyze because the a) models describing them may have many parameters to calibrate or decisions to make and the resulting functions are not convex and b) the objective function is often a simulation model that is expensive (minutes or hours) for each evaluation. This seminar will focus on Prof. Shoemaker’s recent research using RBF surrogate global optimization of expensive multimodal functions and its application to environmental model calibration or decision making. The algorithms (serial or parallel) are general purpose and can be used on expensive, multimodal objective functions (including for simulation optimization unrelated to the environment). Her earlier research (on groundwater, acid rain, and pesticide reduction) and her international organizational efforts to protect groundwater from pollution will also be discussed briefly.
The Institute for Operations Research and the Management Sciences
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