Imperialist Competitive Algorithm (ICA) Approach for Optimization of the Surface Grinding Process

The imperialist Competitive Algorithm (ICA) is one of the recent meta-heuristic algorithms proposed to solve optimization problems. The Imperialist Competitive Algorithm is based on a socio-politically inspired optimization strategy. This paper presents an Imperialist Competitive Algorithm (ICA) to optimize the performance of a surface grinding operation.  Moreover, the multi-objective optimization of a surface grinding process is suggested by using an evolutionary algorithm. Factors like depth of dressing, lead of dressing, workpiece speed and wheel speed are considered to minimize the production cost, surface roughness and to maximize the production rate. The suggested approach presents two constraints handling techniques: constraints handling strategy of ICA and penalty function method. The effectiveness of this algorithm for grinding operation is investigated by comparing the results to other algorithms available in the literature. Results show that the proposed algorithm in this work gives a better performance in a shorter time for the optimization of machining parameters in comparison to other works.

Keywords:

Machining Parameters , Optimization , Surface Grinding , Imperialist competitive algorithm (ICA)