Structural inverse analysis by hybrid simplex artificial bee colony algorithms

Authors:
Fei Kang;Junjie Li;Qing Xu
Affiliations:
School of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian 116024, China;School of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian 116024, China;School of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian 116024, China
Venue:
Computers and Structures
Year:
2009

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Abstract

A hybrid simplex artificial bee colony algorithm (HSABCA) which combines Nelder-Mead simplex method with artificial bee colony algorithm (ABCA) is proposed for inverse analysis problems. The proposed algorithm is applied to parameter identification of concrete dam-foundation systems. To verify the performance of HSABCA, it is compared with the basic ABCA and a real coded genetic algorithm (RCGA) on two examples: a gravity dam and an arc dam. Results show that the proposed algorithm is an efficient tool for inverse analysis and it performs much better than ABCA and RCGA on such problems.