2019
DOI: 10.1007/s11709-019-0543-5
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Optimal dome design considering member-related design constraints

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Cited by 10 publications
(9 citation statements)
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“…In this regard, the design of SDS with various geometrical configurations is optimized thereby utilizing a MOA named Pareto Archived Genetic Algorithm (PAGA) along with the displacement, joint and member-related design constraints. It is noted that the computing performance of PAGA was also evaluated considering several multi-objective evolutionary algorithms named NSGAII [27], SMSEMOA [28], MOEA/D [29], PESAII [30], SPEA2 [31], eMOEA [32], [21].…”
Section: Integration Of An Automatic Dome Generating Tool For Conceptmentioning
confidence: 99%
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“…In this regard, the design of SDS with various geometrical configurations is optimized thereby utilizing a MOA named Pareto Archived Genetic Algorithm (PAGA) along with the displacement, joint and member-related design constraints. It is noted that the computing performance of PAGA was also evaluated considering several multi-objective evolutionary algorithms named NSGAII [27], SMSEMOA [28], MOEA/D [29], PESAII [30], SPEA2 [31], eMOEA [32], [21].…”
Section: Integration Of An Automatic Dome Generating Tool For Conceptmentioning
confidence: 99%
“…Use of an appropriate structural analysis approach Due to the discrete nature of SDS, there exists a high tendency to inherently a significant configurational change in its structural system under any external loading condition. Although the member responses of SDS are well below a yield point of material, the nodal displacements of SDS may suddenly reach to the higher values [19][20][21]. In fact, the larger nodal displacements cause also to be arisen a global stability-related failure in SDS although the stabilities of SDS members are not lost.…”
Section: Introductionmentioning
confidence: 99%
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“…This main loop is terminated once the maximum generation number is completed. The further details about working principle of PAGA are presented in Reference Talaslioglu [22].…”
Section: The Working Mechanism Of Proposed Evolutionary-based Multi-omentioning
confidence: 99%