Large-Scale Truss Topology and Sizing Optimization by an Improved Genetic Algorithm with Multipoint Approximation
| Autor: | Tianshan Dong, Shenyan Chen, Hai Huang, Chao Han, Ziqi Dai, Zihan Yang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Fluid Flow and Transfer Processes
Technology QH301-705.5 Process Chemistry and Technology Physics QC1-999 General Engineering topology optimization large-scale truss label–clip–splice technique a branched multipoint approximation genetic algorithm Engineering (General). Civil engineering (General) Computer Science Applications Chemistry General Materials Science TA1-2040 Biology (General) Instrumentation QD1-999 |
| Zdroj: | Applied Sciences, Vol 12, Iss 407, p 407 (2022) Applied Sciences; Volume 12; Issue 1; Pages: 407 |
| ISSN: | 2076-3417 |
| Popis: | Truss size and topology optimization problems have recently been solved mainly by many different metaheuristic methods, and these methods usually require a large number of structural analyses due to their mechanism of population evolution. A branched multipoint approximation technique has been introduced to decrease the number of structural analyses by establishing approximate functions instead of the structural analyses in Genetic Algorithm (GA) when GA addresses continuous size variables and discrete topology variables. For large-scale trusses with a large number of design variables, an enormous change in topology variables in the GA causes a loss of approximation accuracy and then makes optimization convergence difficult. In this paper, a technique named the label–clip–splice method is proposed to improve the above hybrid method in regard to the above problem. It reduces the current search domain of GA gradually by clipping and splicing the labeled variables from chromosomes and optimizes the mixed-variables model efficiently with an approximation technique for large-scale trusses. Structural analysis of the proposed method is extremely reduced compared with these single metaheuristic methods. Numerical examples are presented to verify the efficacy and advantages of the proposed technique. |
| Databáze: | OpenAIRE |
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