Metaheuristic methods have become a popular tool in solving large scale optimization problem for a variety of biological systems. In this report, we present Max-Min Ant System (MMAS), a class of swarm intelligence metaheuristics approach, in computing transmembrane helical arrangement of the homotetrameric protein, the potassium channel from Streptomyces iividans (KcsA). The MMAS algorithm was employed to solve transmembrane arrangement problems through the use of an objective penalty function based on distance-violated constraints. Assembly structures of the four inner helices of the KcsA channel were computed bythe construction of probability associated with a set of translational and rotational parameters and the four-fold symmetry transformation applied to the atomic coordinates of the rigid single helix. The MMAS parameters including the number of ants, the number of iteration, weight of pheromone, weight of heuristic information, and pheromone evaporation weight were examined. We demonstrated the effectiveness of the present approach, which can correctly generate native-like structure with root-mean square deviation (RMSD) below 3 Å with respect to the x-ray structure.