An Improved Genetic Algorithm for the Optimization of Composite Structures

Abstract

There are many diverse applications that are mathematically modelled in terms of mixed discrete-continuous variables. The optimization of these models is typically difficult due to their combinatorial nature and potential existence of multiple local minima in the search space. Genetic algorithms (GAs) are powerful tools for solving such problems. GAs do not require gradient or Hessian information. However, to reach an optimal solution with a high degree of confidence, they typically require a large number of analyses during the optimization search. Performance of these methods is even more of an issue for problems that include continuous variables. iii DedicationThe author wishes to dedicate this work to the memory of his grandfather, Vladimir Alexandrovich Pticyn , who was a mechanical engineer.iv Acknowledgments

Lay-up optimisation of fibre metal laminates based on fatigue crack propagation and residual strength

“…The closest to the current problem are only optimisation procedures for composite structures in which laminates are designed for buckling or maximum strength [12][13][14][15][16]. These procedures focus mainly on stacking sequence or ply orientation optimisation, which could not be applied to FMLs due to its different build up with the additional metal layers.…”

The Optimization of a Subsea Pipeline Installation Configuration Using a Genetic Algorithm

“…Tabakov in [14] presents an overview of multi-criteria optimization of layered structures using GA. Vieira et al [15] applied GA to optimize the configuration of vertical submarine pipes (risers) and in [16] they compared this application of GA to other optimization algorithms inspired by biological processes. Gantovnik [17] provides an overview of GAs adapted for the optimization of composite structures.…”