Research Repository

Shuffled Complex Evolution Model Calibrating Algorithm: Enhancing its Robustness and Efficiency

Muttil, Nitin and Jayawardena, Arlene (2008) Shuffled Complex Evolution Model Calibrating Algorithm: Enhancing its Robustness and Efficiency. Hydrological Processes, 22 (23). pp. 4628-4638. ISSN 0885-6087

[img]
Preview
Text
08 - Shuffled Complex Evolution Model Calibrating Algor .pdf - Accepted Version

Download (389kB) | Preview

Abstract

Shuffled Complex Evolution—University of Arizona (SCE-UA) has been used extensively and proved to be a robust and efficient global optimization method for the calibration of conceptual models. In this paper, two enhancements to the SCEUA algorithm are proposed, one to improve its exploration and another to improve its exploitation of the search space. A strategically located initial population is used to improve the exploration capability and a modification to the downhill simplex search method enhances its exploitation capability. This enhanced version of SCE-UA is tested, first on a suite of test functions and then on a conceptual rainfall-runoff model using synthetically generated runoff values. It is observed that the strategically located initial population drastically reduces the number of failures and the modified simplex search also leads to a significant reduction in the number of function evaluations to reach the global optimum, when compared with the original SCE-UA. Thus, the two enhancements significantly improve the robustness and efficiency of the SCE-UA model calibrating algorithm.

Item Type: Article
Uncontrolled Keywords: ResPubID14882, evolutionary computation, optimization, calibration, hydrologic models
Subjects: Faculty/School/Research Centre/Department > School of Engineering and Science
FOR Classification > 0905 Civil Engineering
SEO Classification > 9609 Land and Water Management
Related URLs:
Depositing User: VUIR
Date Deposited: 12 Sep 2011 03:53
Last Modified: 07 Feb 2017 10:33
URI: http://vuir.vu.edu.au/id/eprint/3856
DOI: 10.1002/hyp.7082
ePrint Statistics: View download statistics for this item
Citations in Scopus: 8 - View on Scopus

Repository staff only

View Item View Item

Search Google Scholar