Stacking sequence optimization of laminated composite structures using genetic algorithm with local improvement

2004 ◽  
Vol 63 (3-4) ◽  
pp. 339-345 ◽  
Author(s):  
Ching-Chieh Lin ◽  
Ya-Jung Lee
Keyword(s):  
Genetic Algorithm ◽  
Composite Structures ◽  
Laminated Composite ◽  
Stacking Sequence ◽  
Sequence Optimization ◽  
Stacking Sequence Optimization ◽  
Local Improvement ◽  
Laminated Composite Structures

Multiobjective stacking sequence optimization for laminated composite structures

2009 ◽  
Vol 69 (7-8) ◽  
pp. 983-990 ◽  
Author(s):  
François-Xavier Irisarri ◽  
David Hicham Bassir ◽  
Nicolas Carrere ◽  
Jean-François Maire
Keyword(s):  
Composite Structures ◽  
Laminated Composite ◽  
Stacking Sequence ◽  
Sequence Optimization ◽  
Stacking Sequence Optimization ◽  
Laminated Composite Structures

scholarly journals Simultaneous Shape and Stacking Sequence Optimization of Laminated Composite Free-Form Shells Using Multi-Island Genetic Algorithm

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Bingbing San ◽  
Zhi Xiao ◽  
Ye Qiu
Keyword(s):  
Genetic Algorithm ◽  
Discrete Optimization ◽  
Laminated Composite ◽  
Optimization Method ◽  
Free Form ◽  
Stacking Sequence ◽  
Control Points ◽  
Two Phase ◽  
Sequence Optimization ◽  
Stacking Sequence Optimization

A simultaneous shape and stacking sequence optimization algorithm is presented for laminated composite free-form shells, by which the coupled effect of shape and stacking sequence can be considered. The optimization objective is determined as maximizing fundamental natural frequency to obtain largest stiffness of shells. Nonuniform rational B-spline (NURBS) is employed to represent free-form geometrical shapes. The coordinates of NURBS control points and fiber orientations are set up as continuous and discrete optimization variables, respectively, and optimized simultaneously. To improve the efficiency of the mixed continuous-discrete optimization, multi-island genetic algorithm (MIGA) is employed to search for the global result. Through several numerical examples, the performance of the proposed approach is demonstrated in comparison with the two-phase optimization method; the effect of boundary conditions and the setup of control points on optimal results are investigated, respectively.

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