Abstract
A multi-objective robust optimisation (MORO) of carbon and glass fibre-reinforced hybrid composites under flexural loading based on an a posteriori approach has been presented in this paper. The hybrid composite comprised of T700S carbon/epoxy laminate at the tensile side and E glass/epoxy laminate at the compressive side. The conflicting objectives for optimisation were to minimise the cost and weight of the composite subject to the constraint of a minimum specified flexural strength. Fibre angles and thicknesses of each lamina were considered as uncertain but bounded variables with the worst-case analyses being performed as a non-probabilistic method and the effect of uncertainties being determined. A hybrid multi-objective optimisation evolutionary algorithm (MOEA) was introduced through modification of an elitist non-dominated sorting genetic algorithm (NSGA-II) and combining it with the fractional factorial design method. The performance of the hybrid algorithm was found to be superior to that of the original version of NSGA-II. The multi-objective robust optimisation of the hybrid composite was solved by utilising the proposed algorithm for several levels of strength with the robust Pareto optimal sets being generated and compared. Three scenarios have been considered to illustrate the applicability of the obtained solutions in an a posteriori decision making process.
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