This paper presents an algorithm for identifying desirable multiple targets in an intracellular regulation network. The algorithm is based on constrained state feedback and Monte-Carlo simulations. The computational complexity of the algorithm increases linearly with increasing the number of species in a gene regulation system. An estimate is derived for the confidence level of the predicted minimum required perturbation strength when targets are prescribed a priori. The algorithm has been used to analyze the cell cycle of Xenopus frog eggs. The results agree well with available results for single target perturbations, and multi-target interference is usually not equal to the summation of the single-target interferences.