An Improved Genetic Algorithm for the Optimization of Composite Structures
Keyword(s):
This paper describes a new approach for reducing the number of the fitness and constraint function evaluations required by a genetic algorithm (GA) for optimization problems with mixed continuous and discrete design variables. The proposed modification improves the efficiency of the memory constructed in terms of the continuous variables. The work presents the algorithmic implementation of the proposed memory scheme and demonstrates the efficiency of the proposed multivariate approximation procedure for the weight optimization of a segmented open cross section composite beam subjected to axial tension load. Results are generated to demonstrate the advantages of the proposed improvements to a standard genetic algorithm.
2011 ◽
Vol 66-68
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pp. 1167-1172
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2017 ◽
Vol 2017
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pp. 1-12
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1997 ◽
Vol 33
(2)
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pp. 1900-1903
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2014 ◽
Vol 989-994
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pp. 1853-1856
2015 ◽
Vol 14
(01)
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pp. 1550003
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