Optimization of turning process is a non-linear optimization with constrains and it is difficult for theconventional optimization algorithms to solve this problem. The purpose of present study is todemonstrate the potential of Imperialist Competitive Algorithm (ICA) for optimization of multipassturning process. This algorithm is inspired by competition mechanism among imperialists andcolonies, in contrast to evolutionary algorithmsthat perform the exploration and exploitation in thesolution space aiming to efficiently find near optimal solutions using a finite sequence ofinstructions. To validate the proposed approach, the results of ICA were finally compared withGenetic Algorithm (GA).Based on the results; ICA has demonstrated excellent capabilities such assimplicity, accuracy, faster convergence and better global optimum achievement. The outcomeshows the success of ICA in optimizing the machining process indicating that data analysis methoddeveloped in this work can be effectively applied to optimize machining processes. Manuscript profile