Three decades of the Shuffled Complex Evolution (SCE-UA) optimization algorithm: Review and applications
نویسندگان
1 Center for Hydrometeorology and Remote Sensing (CHRS) & Department of Civil and Environmental Engineering, University of California, Irvine, CA, USA
2 Department of Hydrology & Atmospheric Sciences, The University of Arizona, Tucson, AZ, USA
3 Center for Hydrometeorology and Remote Sensing (CHRS) & Department of Civil and Environmental Engineering, University of California, Irvine, CA, USA
4 Faculty of Geographical Sciences, Beijing Normal University, Beijing, China.
5 Center for Hydrometeorology and Remote Sensing (CHRS) & Department of Civil and Environmental Engineering, University of California, Irvine, CA, USA.; Department of Earth System Science, University of California, Irvine, CA, USA.
doi
10.24200/sci.2019.21500چکیده
The Shuffled Complex Evolution (SCE-UA) method developed at the University of Arizona is a global optimization algorithm, initially developed by [1] for the calibrationof conceptual rainfall-runoff (CRR) models. SCE-UA searches for the global optimumof a function by evolving clusters of samples drawn from the parameter space, via a systematiccompetitive evolutionary process. Being a general purpose global optimization algorithm, it has found widespread applications across a diverse range of science and engineering fields. Here, we recount the history of the development of the SCE-UA algorithm and its later advancements. We also present a survey of illustrative applications of the SCE-UA algorithm and discuss its extensions to multi-objective problems and touncertainty assessment. Finally, we suggest potential directions for future investigation.