Efficient truss optimization using the contrast-based fruit fly optimization algorithm

• Published in: Computers & structures Vol. 182; pp. 137 - 148
• Main Authors: Kanarachos, Stratis, Griffin, James, Fitzpatrick, Michael E.
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.04.2017; Elsevier BV
• Subjects: Algorithms; Animal behavior; Brain; Design optimization; Fruit fly optimization; Fruits; Insects; Multi-parameter; Optimization algorithms; Robustness (mathematics); Sensitivity analysis; Smell; Studies; Truss optimization; Visual flight; Visual stimuli; Fruit fly optimization; Multi-parameter; Truss optimization
• ISSN: 0045-7949; 1879-2243
• DOI: 10.1016/j.compstruc.2016.11.005

•Truss optimization using fruit fly optimization algorithm.•Advanced modelling of fruit fly food search behaviour.•Efficiency in truss optimization with frequency constraints.•Intuitive, few tuning parameters. A recent biological study shows that the extremely good efficiency of fruit flies in finding food, despite their small brain, emerges by two distinct stimuli: smell and visual contrast. “contrast-based fruit fly optimization”, presented in this paper, is for the first time mimicking this fruit fly behaviour and developing it as a means to efficiently address multi-parameter optimization problems. To assess its performance a study was carried out on ten mathematical and three truss optimization problems. The results are compared to those obtained using twelve state-of-the-art optimization algorithms and confirm its good and robust performance. A sensitivity analysis and an evaluation of its performance under parallel computing were conducted. The proposed algorithm has only a few tuning parameters, is intuitive, and multi-faceted, allowing application to complex n-dimensional design optimization problems.