Analysis and benchmarking of meta-heuristic techniques for lay-up optimization

• Published in: Computers & structures Vol. 88; no. 5; pp. 272 - 282
• Main Authors: Bloomfield, Mark W., Herencia, J. Enrique, Weaver, Paul M.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.03.2010; Elsevier
• Subjects: ACO; Algorithms; Applied sciences; Benchmarking; Buckling; Colonies; Composites; Computational techniques; Exact sciences and technology; Forms of application and semi-finished materials; Fundamental areas of phenomenology (including applications); Heuristic methods; Laminates; Mathematical methods in physics; Meta-heuristics; Optimization; Particulate composites; Physics; Polymer industry, paints, wood; PSO; Solid mechanics; Stacking; Stacking sequence; Structural and continuum mechanics; Technology of polymers; GA; Stacking sequence; ACO; PSO; Optimization; Meta-heuristics; Stratified material; Constraint; Simple support; Particle swarm optimization; Composite material; Genetic algorithm; Heuristic method; Swarm intelligence; Fiber orientation; Buckling
• ISSN: 0045-7949; 1879-2243
• DOI: 10.1016/j.compstruc.2009.10.007

The analysis and benchmarking of three meta-heuristic algorithms to determine laminate stacking sequences is presented. The benchmarking is undertaken for a simply supported composite laminate subject to strength and buckling constraints. A genetic algorithm, ant colony and particle swarm optimization are considered. It is shown that for inherently discrete sets of ply orientations, ant colony optimization outperforms the other algorithms. For continuous problems, a particle swarm may be the most appropriate. It is further shown that selection of an appropriate algorithm may be indeed problem dependent.