TY - JOUR
T1 - Three decades of the shuffled complex evolution (sce-ua) optimization algorithm
T2 - Review and applications
AU - Naeini, M. Ralinamay
AU - Analui, B.
AU - Gupta, H. V.
AU - Duan, Q.
AU - Soroosliian, S.
N1 - Funding Information:
Qingyun Duan received his PhD in Hydrology from the University of Arizona in 1991. He is currently a Professor and Chief Scientist of hydrology and water resources in the Faculty of Geographical Science at Beijing Normal University in China. His research interests include hydrology and water resources, hydrological model development and calibration, hydrometeorological ensemble forecasting, and uncertainty quanti cation for large complex system models. He has authored or co-authored more than 160 peer reviewed articles and edited 3 books. Dr. Duan has been active in many international scienti c activities, including serving as the co-leader of the Model Parameter Estimation Experiment (MOPEX) and a member of the scienti c steering committees of the Global Energy and Water Exchanges (GEWEX) Project and the Hydrological Ensemble Prediction Experiment (HEPEX). He has been serving as an editor or editorial board member for numerous scienti c journals, including Reviews of Geophysics, Bulleting of American Meteorological Society, and Water Resources Research. Dr. Duan is a recipient of Chinese Government \One-Thousand Talents Program" Award and a Fellow of American Geophysical Union and American Meteorological Society.
Publisher Copyright:
©2019 Sharif University of Technology. All rights reserved.
PY - 2019
Y1 - 2019
N2 - The Shuffled Complex Evolution (SCE-UA) method developed at the University of Arizona is a global optimizat ion algorithm, initially developed by Duan et. al. [Duan, ()., Sorooshian, S., and Gupta, V. "Effective and efficient global optimization for conceptual rainfall-runoff models", Water Resources Research.4 28(4), pp. 1015-1031 (1992)]. for the calibration of Conceptual Rainfall-Runoff (CRR) models. SCE-UA searches for the global optimum of a function by evolving clusters of samples drawn from the parameter space, via a systematic competitive 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 to uncertainty assessment. Finally, we suggest potential directions for future investigation.
AB - The Shuffled Complex Evolution (SCE-UA) method developed at the University of Arizona is a global optimizat ion algorithm, initially developed by Duan et. al. [Duan, ()., Sorooshian, S., and Gupta, V. "Effective and efficient global optimization for conceptual rainfall-runoff models", Water Resources Research.4 28(4), pp. 1015-1031 (1992)]. for the calibration of Conceptual Rainfall-Runoff (CRR) models. SCE-UA searches for the global optimum of a function by evolving clusters of samples drawn from the parameter space, via a systematic competitive 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 to uncertainty assessment. Finally, we suggest potential directions for future investigation.
KW - Evolutionary algorit hm
KW - Hydrology
KW - Mult i-object ive
KW - Optimizat ion
KW - Shuffled complex evolution, sce-ua
KW - Uncertainty assessment
KW - Water resources
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U2 - 10.24200/sci.2019.21500
DO - 10.24200/sci.2019.21500
M3 - Review article
AN - SCOPUS:85073471708
VL - 26
SP - 2015
EP - 2031
JO - Scientia Iranica
JF - Scientia Iranica
SN - 1026-3098
IS - 4A
ER -