期刊
ENGINEERING OPTIMIZATION
卷 50, 期 10, 页码 1645-1661出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/0305215X.2017.1417400
关键词
Truss optimization; differential evolution; grey wolf optimization; hybrid evolutionary algorithms; adaptive evolutionary algorithms; fully stressed design
资金
- Royal Golden Jubilee PhD Program [PHD/0130/2557]
- Thailand Research Fund [BRG5880014]
A hybrid adaptive optimization algorithm based on integrating grey wolf optimization into adaptive differential evolution with fully stressed design (FSD) local search is presented in this article. Hybrid reproduction and control parameter adaptation strategies are employed to increase the performance of the algorithm. The proposed algorithm, called fully stressed design-grey wolf-adaptive differential evolution (FSD-GWADE), is demonstrated to tackle a variety of truss optimization problems. The problems have mixed continuous/discrete design variables that are assigned as simultaneous topology, shape and sizing design variables. FSD-GWADE provides competitive results and gives superior results at a higher success rate than the previous FSD-based algorithm.
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