In this paper a revised algorithm, derived by the Stud GA, to optimize the stacking sequence of layered composite structures is presented. The constrained combinatorial problem is formulated and hence solved by means of the algorithm presented herein. Unlike the Stud GA, the proposed algorithm uses a fitness-proportionate selection to find potential mates to the Stud and a self-adaptive extinction to avoid premature convergence. Elitism is also allowed. Standard benchmark problems have been used to fully assess the validity of the proposed algorithm. Results in terms of reliability and efficiency are compared against three GAs and a Permutation Search (PS) algorithm. It has been demonstrated, by means of a parametric study, that a low probability of extinction is sufficient to ensure fast convergence as well as reliable results. Finally the optimization of a more complex aeronautic structure is addressed aiming to prove the validity of the proposed algorithm in a two level optimization strategy. Results in terms of efficiency are compared against those of an in-house standard GA. © 2016 Springer-Verlag Berlin Heidelberg
Constrained combinatorial optimization of multi-layered composite structures by means of Stud GA with proportionate selection and extinction / Danzi, Francesco; Frulla, Giacomo; Cestino, Enrico. - In: STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION. - ISSN 1615-1488. - 55:6(2017), pp. 2239-2257. [10.1007/s00158-016-1638-4]
Constrained combinatorial optimization of multi-layered composite structures by means of Stud GA with proportionate selection and extinction
DANZI, FRANCESCO;FRULLA, Giacomo;CESTINO, ENRICO
2017
Abstract
In this paper a revised algorithm, derived by the Stud GA, to optimize the stacking sequence of layered composite structures is presented. The constrained combinatorial problem is formulated and hence solved by means of the algorithm presented herein. Unlike the Stud GA, the proposed algorithm uses a fitness-proportionate selection to find potential mates to the Stud and a self-adaptive extinction to avoid premature convergence. Elitism is also allowed. Standard benchmark problems have been used to fully assess the validity of the proposed algorithm. Results in terms of reliability and efficiency are compared against three GAs and a Permutation Search (PS) algorithm. It has been demonstrated, by means of a parametric study, that a low probability of extinction is sufficient to ensure fast convergence as well as reliable results. Finally the optimization of a more complex aeronautic structure is addressed aiming to prove the validity of the proposed algorithm in a two level optimization strategy. Results in terms of efficiency are compared against those of an in-house standard GA. © 2016 Springer-Verlag Berlin HeidelbergPubblicazioni consigliate
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https://hdl.handle.net/11583/2661543
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