Optimization of machining parameters for parallel turnings using estimation of distribution algorithms

Optimal machining parameters can lead to considerable savings in manufacturing problems. In this paper, to deal with the nonlinear optimization problem of machining parameters which aims to minimize the unit production cost (UC) in parallel turnings, we propose a novel optimization approach which divides this complicated problem into several sub-problems. Then an estimation of distribution algorithm (EDA) is developed to search the optimal results for each sub-problem. Computer simulations show that the proposed approach is efficient in searching the optimal solutions to reduce significantly the unit production cost.