In this study, part selection and machine loading problems of FMS planning phase are handled and expressed as a bi-objective mixed integer programming model which is solved sequentially. Unfortunately, the combinatorial structure of the problem makes the solution difficult and time consuming for real-world size problems by using the mathematical models. Therefore, a tabu search algorithm supported by an intensification and a diversification strategy is developed to solve the problem. The performance of the algorithm, for which the best parameter set is determined by factorial design analysis, is tested on the random generated problems with different sizes. The results are compared with those of the mathematical model.