Abstract: The standard ant system is suitable for the discrete optimization problem, but it lacks special mechanism for dealing with constraints.In this paper, a constrained ant colony system(CACS) for solving constraint-handling optimization problem was proposed, which was based on the biology behavior of ant colony foraging and the heuristic rules for estimating the quality of food source.The mechanism of group recruitment and mass recruitment, which were used to guide the ant colony to search the best solution in the feasible region, were embedded to the ant colony system.To illustrate the effectiveness of proposed algorithm, two benchmark functions were used, the results demonstrated better performance of CACS for achieving global optimal.Furthermore, CACS was applied to the process optimization of butene alkylation.The satisfactory result demonstrated the effectiveness of CACS.