期刊
ENGINEERING WITH COMPUTERS
卷 35, 期 2, 页码 721-740出版社
SPRINGER
DOI: 10.1007/s00366-018-0629-z
关键词
Truss optimization; Multi-objective evolutionary algorithms; Pareto dominance; Reliability index
资金
- Graduate Engineering Camp Fund, Faculty of Engineering, Khon Kaen University, Thailand
- Thailand Research Fund (TRF)
This paper proposes the design of trusses using simultaneous topology, shape, and size design variables and reliability optimization. Objective functions consist of structural mass and reliability, while the probability of failure is set as a design constraint. Design variables are treated to simultaneously determine structural topology, shape, and sizes. Six test problems are posed and solved by a number of multi-objective evolutionary algorithms, and it is found that Hybridized Real-Code Population-Based Incremental Learning and Differential Evolution is the best performer. This work is considered an initial study for the combination of reliability optimization and simultaneous topology, shape, and sizing optimization of trusses.
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