Multi-pass turning operations optimization based on genetic algorithms

The paper proposes a new optimization technique based on genetic algorithms for determination of the cutting parameters in multi-pass machining operations by simultaneously considering multi-pass rough machining and finish machining. The optimum machining parameters are determined by minimizing the unit production cost subject to twenty practical machining constraints. The cutting model formulated is a non-linear, constrained programming problem. Experimental results show that the proposed genetic algorithm based approach is both effective and efficient.