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Hybrid genetic algorithm and particle swarm optimization for the force method-based simultaneous analysis and design | ||
| Iranian Journal of Science and Technology Transactions of Civil Engineering | ||
| شناسنامه علمی شماره، دوره 34، شماره 1، فروردین 2010، صفحه 15-34 اصل مقاله (432.56 K) | ||
| شناسه دیجیتال (DOI): 10.22099/ijstc.2012.680 | ||
| چکیده | ||
| The computational drawbacks of existing numerical methods have forced researchers to rely on heuristic algorithms. Heuristic methods are powerful in obtaining the solution of optimization problems. Although these methods are approximate methods (i.e. their solutions are good, but probably not optimal), they do not require the derivatives of the objective function and constraints. Also, the heuristics use probabilistic transition rules instead of deterministic rules. Here, an evolutionary algorithm based on the hybrid genetic algorithm (GA) and particle swarm optimization (PSO), denoted by HGAPSO, is developed in order to solve force method-based simultaneous analysis and design problems for frame structures. Suitability of the HGAPSO algorithm is compared to both GA and PSO for all the design examples, demonstrating its efficiency and superiority, especially for frames with a larger number of redundant forces. | ||
| کلیدواژهها | ||
| Simultaneous analysis and design؛ Force method؛ trusses؛ frames؛ hybrid genetic algorithm and particle swarm optimization | ||
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آمار تعداد مشاهده مقاله: 1,564 تعداد دریافت فایل اصل مقاله: 2,979 |
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