This paper describes the implementation of a parallel Tabu Search algorithm for multi-objective continuous optimisation problems. We compare our new algorithm with a leading multi-objective Genetic Algorithm and find it exhibits comparable performance on standard benchmark problems. In addition, for certain problem types, we expect Tabu Search to outperform other algorithms and present preliminary results from an aerodynamic shape optimisation problem. This is a real-world, highly constrained, computationally demanding design problem which requires efficient optimisation algorithms that can be run on parallel computers: with this approach optimisation algorithms are able to play a part in the design cycle.