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1 Shuffled Complex Evolution method (SCE-UA) A global optimization algorithm J. Nossent.

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1 1 Shuffled Complex Evolution method (SCE-UA) A global optimization algorithm J. Nossent

2 Pag. 2 Global optimization Optimize OF over ENTIRE parameter space –RANDOM sampling (deal with local optimums) –SLOWER than local methods (2000 – runs) SCE-UA –Widespread in hydrology –Implemented in SWAT2005 –Information sharing by SHUFFLING key to efficient algorithm

3 Pag. 3 SCE-UA Developed at the University of Arizona (UA) Combines strength of: –Nelder-Mead (simplex) –Controlled random search –Genetic algorithms –Complex shuffling

4 Pag. 4 SCE-UA Complex: –subgroup of sample set Ω: –Parameter space

5 Pag. 5 SCE-UA

6 Pag. 6 SCE-UA

7 Pag. 7 SCE-UA

8 Pag. 8 SCE-UA

9 Pag. 9 SCEM-UA SCE-UA + Metropolis algorithm –No longer to small area –Allows simulation of posterior density Metropolis –MCMC –Replaces Simplex method

10 Pag. 10 References SCE-UA –Duan, Q., Gupta, V.K. and Sorooshian, S., A shuffled complex evolution approach for effective and efficient global optimization, J.,Optim. Theory Appl., 76, p –Sorooshian, S. and Gupta, K.V., 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., A Shuffled Complex Evolution Metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters, Water Resour. Res., 39 (8), 1201, doi: /2002WR –Vrugt, J. A., H. V. Gupta, L. A. Bastidas, W. Bouten and S. Sorooshian, Effective and efficient algorithm for multi objective optimization of hydrologic models, Water Resour. Res., 39 (8), 1214, doi: /2002WR001746


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