Hossein Towsyfyan - Department of Manufacturing Engineering, Arvandan Nonprofit Higher Education Institute, Khorramshahr, Iran
Seyed Adnan Adnani Salehi - Department of Manufacturing Engineering, Arvandan Nonprofit Higher Education Institute, Khorramshahr, Iran
Majed Ghayyem - Department of Manufacturing Engineering, Arvandan Nonprofit Higher Education Institute, Khorramshahr, Iran
Farid Mosaedi - Department of Manufacturing Engineering, Arvandan Nonprofit Higher Education Institute, Khorramshahr, Iran

Optimization of machining parameters is a non-linear optimization with constrains and it is difficult for the conventional optimization algorithms to solve this problem. The purpose of this study is to demonstrate the potential of Imperialist Competitive Algorithm (ICA) for optimization of turning process. This algorithm is inspired by competition mechanism among Imperialists and colonies, in contrast to evolutionary algorithms. To validate the proposed approach, the results of ICA were finally compared with Genetic Algorithm (GA). Based on the results; ICA has demonstrated excellent capabilities such as simplicity, accuracy, faster convergence and better global optimum achievement. The outcome shows the success of ICA in optimizing the machining conditions

Imperialist competitive algorithm, machining process