In this research, the clonal selection algorithm and an ant colony system are combined to propose an immune ant colony system algorithm to solve unequal-area facility layout problems using a flexible bay structure representation. Clonal selection algorithm operations are introduced in the ant colony system to improve the convergence speed of the ant colony system and increase the differences among ant solutions. The search capability of the immune ant colony system is thus enhanced. Datasets for well-known benchmark problems were used to evaluate the effectiveness of this approach. Compared with previous research efforts, the immune ant colony system can offer better solutions in a shorter timeframe for most benchmark problems.