Genetic Algorithm Optimization of Operating Parameters for Multiobjective Multipass End Milling
نویسندگان
چکیده
Genetic Algorithm are capable of handling a large number of design parameters and work for optimization problems that have discontinues or non-differentiable multidimensional solution spaces, making them ideal for optimization of machining parameters. Current paper is based on Genetic Algorithm (GA) for optimization of process parameters (e.g. feed and speed) for multi-objective multi pass end milling. GA has been implemented using the MATLAB environment on the objective function, which is a hybrid function of cost and time, feed and speed. The results of optimum cost, feed and speed have been calculated after GA based implementation with PSO based implementation and conventional results. The GA results are found better in terms of the objective function as compared with PSO results for the multi-objective multipass end milling process.
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