Parameter-less population pyramid for large-scale tower optimization
- Publisher:
- PERGAMON-ELSEVIER SCIENCE LTD
- Publication Type:
- Journal Article
- Citation:
- Expert Systems with Applications, 2018, 96, pp. 175-184
- Issue Date:
- 2018-04-15
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
| 1-s2.0-S0957417417308035-main.pdf | Published version | 1.78 MB |
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The parameter-less population pyramid (P3) is a recent evolutionary computation algorithm proposed for black box optimization. Shown to be efficient for a variety of benchmark problems, P3 replaces the conventional constant population model with expanding sets of expanding populations. We investigated how this new metaheuristic optimization algorithm would transfer to optimize large-scale tower structure problems involving different constraints: geometric and mechanical. P3 is examined by optimizing two discrete tower design problems, 26-story and 35- story tower structures. The performance of P3 is compared with other well-known evolutionary algorithms for black-box optimization including random restart hill climbing, parameter-less hierarchical Bayesian optimization algorithm, differential evolution, and a modified genetic algorithm. The results show that does P3 not only finds the best final solutions, but it also reaches high quality solutions much faster than the other algorithms This fast optimization is vital for the tedious and large-scale structural engineering problems. Finally, the unique search features used in the P3 and the implications for future studies are discussed.
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