A tabu search algorithm is proposed for finding the Pareto solutions of multiobjective optimal design problems. In this paper, the contact theorem is used to evaluate the Pareto solutions. The ranking selecting approach and the fitness sharing function are also introduced to identify new current points to begin every iteration cycle. Detailed numerical results are reported in this paper to demonstrate the power of the proposed algorithm in ensuring uniform sampling and obtaining the Pareto optimal front of the multiobjective design problems. The most efficient method of implementing the proposed algorithm is also discussed.