A modified ant colony algorithm for the stacking sequence optimisation of a rectangular laminate.

This paper presents a modified Ant Colony Algorithm(ACA) called multi-city-layer ant colony algorithm(MCLACA). The research attention is focused on improvingthe computational efficiency in the stacking sequenceoptimisation of a laminated composite plate for maximumbuckling load. A new operator, the so-called two point interchange,is introduced and proved to be effective for reducingthe convergence time and enhancing the robustness in theMCLACA performance. The laminate optimisation is subjectto balanced and symmetric layup with ply contiguousand strength constraints. In order to assess the MCLACAperformance, a simply supported rectangular laminate plate,which was taken as numerical example in previous researchusing traditional ACA and genetic algorithm (GA) is chosenas a benchmark case study. Comparing with the ACAand GA results, it is shown that the presented MCLACAhas better performance in terms of computational efficiencyand robustness. To demonstrate the applicability of theMCLACA to a general case, an additional example of laminateoptimisation has been taken with more design variablesand five different boundary conditions by finite elementanalysis. [ABSTRACT FROM AUTHOR]