The offshore hydrocarbon industry operates in more hostile environments as more of marginal fields become economically viable. This means that more floating production systems and economical mooring systems will be needed. With this increase in the use of marginal fields goes the need to re-use vessels and moorings. Floating production systems, such as FPSO's, need to survive extreme events and extreme damage conditions. When one mooring line is damaged, the remaining ones must be sufficient to avoid a complete failure and still protect critical components such as the riser. This paper looks into applying an evolutionary optimisation technique, namely multiple objective particle swarm optimisation, to the damaged mooring design and analysis. The evaluation of offshore objective functions is computationally expensive since it requires use of complex simulations. When the number of objective function evaluations is large, as is the case with evolutionary methods, even a fast computer takes undesirably long to complete the job. Hence, a robust optimisation algorithm with great efficiency is required to minimise the number of total runs.