Abstract: The mathematical problems of fuzzy dependent-chance programming (FDCP) pose significant computational challenges due to their non-linear, non-convex, and fuzzy nature. A fuzzy simulation based algorithm is designed for solving the random FDCP problem. The proof of convergence is developed. The convergence speed of the ant colony optimization (ACO) algorithm is analyzed by estimating the expected convergence time. A numerical example is presented to show the potential applications of the random programming as well as the efficiency, stability and accuracy of the proposed algorithm.