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Shuffled Complex Evolution method (SCE-UA) A global optimization algorithm. J. Nossent. Global optimization. Optimize OF over ENTIRE parameter space RANDOM sampling (deal with local optimums) SLOWER than local methods (2000 – 10 000 runs) SCE-UA Widespread in hydrology
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Shuffled Complex Evolution method (SCE-UA)A global optimization algorithm J. Nossent
Global optimization • Optimize OF over ENTIRE parameter space • RANDOM sampling (deal with local optimums) • SLOWER than local methods (2000 – 10 000 runs) • SCE-UA • Widespread in hydrology • Implemented in SWAT2005 • Information sharing by SHUFFLING key to efficient algorithm
SCE-UA • Developed at the University of Arizona (UA) • Combines strength of: • Nelder-Mead (simplex) • Controlled random search • Genetic algorithms • Complex shuffling
SCE-UA • Complex: • subgroup of sample set • Ω: • Parameter space
SCEM-UA • SCE-UA + Metropolis algorithm • No longer to small area • Allows simulation of posterior density • Metropolis • MCMC • Replaces Simplex method
References • SCE-UA • Duan, Q., Gupta, V.K. and Sorooshian, S., 1993. A shuffled complex evolution approach for effective and efficient global optimization, J.,Optim. Theory Appl., 76, p501-521 • Sorooshian, S. and Gupta, K.V., 1995. Model Calibration. In: Computer models of watershed hydrology, chapter 2 . Singh, V.P. (editor).Water resources publications • SCEM-UA • Vrugt, J. A., Gupta, H.V., Bouten, W. and Sorooshian, S., 2003. A Shuffled Complex Evolution Metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters, Water Resour. Res., 39 (8), 1201, doi:10.1029/2002WR001642 • Vrugt, J. A., H. V. Gupta, L. A. Bastidas, W. Bouten and S. Sorooshian, 2003. Effective and efficient algorithm for multi objective optimization of hydrologic models, Water Resour. Res., 39 (8), 1214, doi:10.1029/2002WR001746