2007
DOI: 10.1016/j.compstruct.2005.06.009
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Application of genetic algorithm for optimum design of bolted composite lap joints

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Cited by 35 publications
(9 citation statements)
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“…The large number of variables within any joint design makes it difficult and expensive to test even a small range of joints comprehensively. Therefore many attempts have been made to understand and predict the failure of composite joints [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25] using numerical and analytical methods to reduce the experimental effort required. Most successful joint modelling has been conducted with slow design tools, i.e.…”
mentioning
confidence: 99%
“…The large number of variables within any joint design makes it difficult and expensive to test even a small range of joints comprehensively. Therefore many attempts have been made to understand and predict the failure of composite joints [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25] using numerical and analytical methods to reduce the experimental effort required. Most successful joint modelling has been conducted with slow design tools, i.e.…”
mentioning
confidence: 99%
“…However in most cases [12][13][14] the focus is always on a specific joint problem and a numerical approach (e.g. the genetic algorithm) is normally used to find an optimum solution.…”
Section: Bolted Joint Connectionsmentioning
confidence: 99%
“…Upon review of the optimization techniques available in the literature, the genetic algorithm (GA) was selected to stochastically guide the algorithm through the solution space of available designs and to arrive at an evolved one [2][3][4][5][6]. In the literature, the GA is a form of artificial evolution and is a commonly used method for optimization [7][8][9][10][11]. A Darwinian "survival of the fittest" approach has been employed to search for optima in large multidimensional spaces [13,14].…”
Section: Introductionmentioning
confidence: 99%