HR: 16:30h
AN: H14A-03    [Abstracts]
TI: Global Optimization With a Limited Budget of Function Evaluations
AU: Sorooshian, S
EM: soroosh@uci.edu
AF: Department of Civil and Environmental Engineering, University of California, Irvine, E 4130 Engineering Gateway, Irvine, CA 92697, United States
AU: * Behrangi, A
EM: abehrang@uci.edu
AF: Department of Civil and Environmental Engineering, University of California, Irvine, E 4130 Engineering Gateway, Irvine, CA 92697, United States
AU: Khakbaz, B
EM: bkhakbaz@uci.edu
AF: Department of Civil and Environmental Engineering, University of California, Irvine, E 4130 Engineering Gateway, Irvine, CA 92697, United States
AU: Vrugt, J A
EM: vrugt@lanl.gov
AF: Center for NonLinear Studies (CNLS), Los Alamos National Laboratory, Mail Stop T003, Los Alamos, NM 87545, United States
AU: Duan, Q
EM: qduan@llnl.gov
AF: Atmospheric, Earth & Energy Department, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA 94551, United States
AB: Selection of a computationally efficient and robust optimization algorithm has always been a key consideration for calibration of watershed simulation models. This goal was the primary reason for the development of the Shuffled Complex Evolution (SCE-UA) algorithm by Duan et al. in the early 1990s. The widely used SCE-UA algorithm was developed with the aim of finding global optimal solutions within the feasible parameter domain. Recently, Tolson and Shoemaker introduced a stochastic neighborhood search algorithm, entitled Dynamically Dimensioned Search (DDS) capable of finding good parameter combinations fast. In their work, it was determined that DDS is a more computationally efficient and robust optimization algorithm than SCE-UA in the context of distributed watershed model automatic calibration. In this talk, we will demonstrate that it is possible to significantly increase the convergence rate of SCE-UA by simple modification of the values of the algorithmic parameters. It is shown that a much faster initial decay of the objective function can be achieved when the reflection and contraction step lengths in the Simplex method are changed from their default values. Our studies clearly show that the modified SCE-UA is the preferred method of choice to find high quality parameter solutions with a limited budget of function evaluations.
DE: 1800 HYDROLOGY
DE: 1846 Model calibration (3333)
SC: Hydrology [H]
MN: 2007 Fall Meeting