Ant Colony Optimization (ACO) is a multi-agent approach, and its search process in each cycle is random. Therefore, some design problems can be simulated using the ACO algorithm. Due to its randomness, the ACO is not an efficient approach to obtain a "Rigid" state of structures that usually being the main objective in the structural optimization problems. On the other hand, Evolutionary Structural Optimization (ESO) is a method based on the evolutionary process in nature which is proved to be suitable for solving structural optimization problems. This study proposed a new combined optimization algorithm, called an Evolutionary Ant Colony Optimization (EACO). The EACO is an improvement of the ACO algorithm by using the innovating ESO strategy to solve structural optimization problems. The effectiveness of the proposed EACO is verified by solving shape optimization problems of plane truss examples.