Hybrid enhanced genetic algorithm to select optimal machining parameters in turning operation

The current paper presents a hybrid enhanced genetic algorithm that is developed for solving the optimization problems in design and manufacturing. The present approach is applied to optimize turning operation for the determination of cutting parameters considering minimum production cost under a set of machining constraints. A refined design space for population is introduced by integrating the robust parameter design concept into the genetic algorithm to solve multi-objective and single-objective optimization problems. First, the proposed approach is validated using test problems and metrics taken from literature. Finally, it is applied to the turning optimization problem. The computational experimental results show the effectiveness of the proposed approach in the turning optimization problem.